Statistical models for longitudinal biomarkers of disease onset
We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fu...
Saved in:
| Published in | Statistics in medicine Vol. 19; no. 4; pp. 617 - 637 |
|---|---|
| Main Authors | , |
| Format | Journal Article Conference Proceeding |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
29.02.2000
Wiley |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0277-6715 1097-0258 |
| DOI | 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R |
Cover
| Abstract | We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data. Copyright © 2000 John Wiley & Sons, Ltd. |
|---|---|
| AbstractList | We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data.We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data. We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data. We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data. Copyright © 2000 John Wiley & Sons, Ltd. |
| Author | Turnbull, Bruce W. Slate, Elizabeth H. |
| Author_xml | – sequence: 1 givenname: Elizabeth H. surname: Slate fullname: Slate, Elizabeth H. email: slate@orie.cornell.edu organization: School of Operations Research and Industrial Engineering and Department of Statistical Science, 206 Rhodes Hall, Cornell University, Ithaca, NY 14853-3801, U.S.A – sequence: 2 givenname: Bruce W. surname: Turnbull fullname: Turnbull, Bruce W. organization: School of Operations Research and Industrial Engineering and Department of Statistical Science, 206 Rhodes Hall, Cornell University, Ithaca, NY 14853-3801, U.S.A |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1318969$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/10694740$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFkV1v0zAUhi00xLrCX0C5QGi7SDn-SBwXBEyBlUqDohUE4ubIcewpkMYjTgX797hKN5BAwhe2dPz6sY-fI3LQ-c4S8pLCjAKwJ8frZbk8oaBkCiwrjhnEwZg6oWounuVUzueny1fpevmW5_Ccz2BWrp6y9OIOmdweOiATYFKmuaTZITkK4SsApRmT98ghhVwJKWBCXqwHPTRhaIxuk42vbRsS5_uk9d1lM2zrpov1qvEb3X-zfUi8S-omWB1s4rtgh_vkrtNtsA_265R8PHv9oXyTnq8Wy_L0PDWCF5BKkZlKWK54xbRhmVUOtKniDM7wWmW54nlFjRHUGQairnKnXV0oLeOOlXxKHo_cq95_39ow4KYJxrat7qzfBpSgBKUgYvDhPritNrbGq76Jb7_Gm5Zj4NE-oENs2vW6M034neO0UPHOKfk8xkzvQ-it-4OEO0mIO0m4-2_c_TfeSEKqUGCUhBgl4SgJOQKWK2R4EdFfRvSPprXXf3H_i_0ndV-J8HSER6n25y086sNccpnhp3cLfH8mFywXBRb8F5gZs0Y |
| Cites_doi | 10.1111/j.2517-6161.1982.tb01203.x 10.1109/TPAMI.1984.4767596 10.2307/2986119 10.2307/2530374 10.1002/(SICI)1097-0258(19970215)16:3<239::AID-SIM483>3.0.CO;2-X 10.1007/BF00128468 10.2307/2530699 10.1002/(SICI)1097-0258(19970215)16:3<259::AID-SIM484>3.0.CO;2-S 10.1002/0471725315 10.2307/2529876 10.2307/2347570 10.1056/NEJM199104253241702 10.1093/jnci/87.5.354 10.1093/biomet/84.1.45 10.1080/01621459.1994.10476806 10.1016/0021-9681(80)90074-0 10.1093/biomet/62.2.407 10.1093/biomet/70.1.111 10.1007/978-1-4684-0192-9 10.1001/jama.1997.03540420052029 10.1002/sim.4780130520 10.1093/biomet/42.3-4.523 10.1002/sim.4780111408 10.2307/2532087 10.1093/biomet/57.1.1 10.1001/jama.1996.03540240035027 10.1093/biomet/56.3.495 10.2307/2533439 10.1001/jama.1993.03510080052031 10.1111/j.2517-6161.1977.tb01600.x 10.1093/biomet/80.1.153 10.2307/2531144 10.1001/jama.1992.03480160073037 10.1080/01621459.1995.10476485 10.1080/01621459.1992.10475258 10.2307/2986089 10.1007/BF00128469 10.1200/JCO.1996.14.11.2889 10.1080/01621459.1991.10475130 10.2307/2533281 10.1080/01621459.1995.10476487 10.2307/2531905 10.1002/(SICI)1097-0258(19981130)17:22<2563::AID-SIM952>3.0.CO;2-O 10.2307/2530523 10.1002/(SICI)1097-0258(19970715)16:13<1515::AID-SIM572>3.0.CO;2-1 10.2307/2987598 10.1080/01621459.1988.10478639 10.1080/01621459.1990.10476213 |
| ContentType | Journal Article Conference Proceeding |
| Copyright | Copyright © 2000 John Wiley & Sons, Ltd. 2000 INIST-CNRS Copyright 2000 John Wiley & Sons, Ltd. |
| Copyright_xml | – notice: Copyright © 2000 John Wiley & Sons, Ltd. – notice: 2000 INIST-CNRS – notice: Copyright 2000 John Wiley & Sons, Ltd. |
| DBID | BSCLL AAYXX CITATION IQODW CGR CUY CVF ECM EIF NPM 7X8 |
| DOI | 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R |
| DatabaseName | Istex CrossRef Pascal-Francis Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine Statistics Public Health |
| EISSN | 1097-0258 |
| EndPage | 637 |
| ExternalDocumentID | 10694740 1318969 10_1002__SICI_1097_0258_20000229_19_4_617__AID_SIM360_3_0_CO_2_R SIM360 ark_67375_WNG_PF7G2648_8 |
| Genre | article Research Support, U.S. Gov't, Non-P.H.S Research Support, U.S. Gov't, P.H.S Journal Article |
| GrantInformation_xml | – fundername: National Science Foundation funderid: DMS 9505065 – fundername: National Institutes of Health funderid: R01 CA66218; R01 CA61120; R01 CA79080 – fundername: Mathematical Research Institute Oberwolfach – fundername: NCI NIH HHS grantid: R01 CA79080 – fundername: NCI NIH HHS grantid: R01 CA66218 – fundername: NCI NIH HHS grantid: R01 CA61120 |
| GroupedDBID | --- .3N .GA .Y3 05W 0R~ 10A 123 1L6 1OB 1OC 1ZS 31~ 33P 3SF 3WU 4.4 4ZD 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 53G 5RE 5VS 66C 6PF 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 930 A03 AAESR AAEVG AAHQN AAMMB AAMNL AANHP AANLZ AAONW AASGY AAWTL AAXRX AAYCA AAZKR ABCQN ABCUV ABIJN ABJNI ABOCM ABPVW ACAHQ ACBWZ ACCZN ACGFS ACPOU ACRPL ACXBN ACXQS ACYXJ ADBBV ADEOM ADIZJ ADKYN ADMGS ADNMO ADOZA ADXAS ADZMN AEFGJ AEIGN AEIMD AENEX AEUYR AEYWJ AFBPY AFFNX AFFPM AFGKR AFWVQ AFZJQ AGQPQ AGXDD AGYGG AHBTC AHMBA AIDQK AIDYY AITYG AIURR AJXKR ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN ALVPJ AMBMR AMYDB ASPBG ATUGU AUFTA AVWKF AZBYB AZFZN AZVAB BAFTC BDRZF BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BSCLL BY8 CS3 D-E D-F DCZOG DPXWK DR2 DRFUL DRSTM DU5 EBS EJD EX3 F00 F01 F04 F5P FEDTE G-S G.N GNP GODZA H.T H.X HBH HGLYW HHY HHZ HVGLF HZ~ IX1 J0M JPC KQQ LATKE LAW LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LW6 LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NF~ NNB O66 O9- OIG P2P P2W P2X P4D PALCI PQQKQ Q.N Q11 QB0 QRW R.K ROL RX1 SUPJJ TN5 UB1 V2E W8V W99 WBKPD WH7 WIB WIH WIK WJL WOHZO WOW WQJ WXSBR WYISQ XBAML XG1 XV2 YHZ ZGI ZZTAW ~IA ~WT AAHHS ACCFJ AEEZP AEQDE AEUQT AFPWT AIWBW AJBDE RWI WRC WUP WWH AAYXX CITATION ABEML ACSCC AGHNM DUUFO EBD EMOBN HF~ IQODW M67 RIWAO RJQFR RYL SAMSI SV3 ZXP CGR CUY CVF ECM EIF NPM 7X8 |
| ID | FETCH-LOGICAL-c4380-745cb4e393b2ac25e9f0acb9f00fc3d956936b1cc41fc204db6fafd89a7693e73 |
| IEDL.DBID | DR2 |
| ISSN | 0277-6715 |
| IngestDate | Fri Jul 11 05:04:14 EDT 2025 Mon Aug 18 09:42:56 EDT 2025 Wed Apr 02 07:25:31 EDT 2025 Tue Jul 01 04:32:45 EDT 2025 Wed Jan 22 16:25:54 EST 2025 Tue Sep 09 05:32:22 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Disease development Bayes estimation Human Urinary system disease Prostate disease Biological marker Change point Malignant tumor Hierarchized structure Prostate specific antigen Onset time Regression model Statistical model Receiver operating characteristic curves Longitudinal distribution Maximum likelihood Male genital diseases Prostate Monitoring |
| Language | English |
| License | http://doi.wiley.com/10.1002/tdm_license_1.1 CC BY 4.0 Copyright 2000 John Wiley & Sons, Ltd. |
| LinkModel | DirectLink |
| MeetingName | Selected papers from the Oberwolfach Conference on Medical Statistics: Mathematical Models for Diagnosis and Prognosis |
| MergedId | FETCHMERGED-LOGICAL-c4380-745cb4e393b2ac25e9f0acb9f00fc3d956936b1cc41fc204db6fafd89a7693e73 |
| Notes | National Institutes of Health - No. R01 CA66218; No. R01 CA61120; No. R01 CA79080 National Science Foundation - No. DMS 9505065 ark:/67375/WNG-PF7G2648-8 ArticleID:SIM360 istex:1388A3997163FAB54C8E1DA69053E9E434551EB6 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| PMID | 10694740 |
| PQID | 70941104 |
| PQPubID | 23479 |
| PageCount | 21 |
| ParticipantIDs | proquest_miscellaneous_70941104 pubmed_primary_10694740 pascalfrancis_primary_1318969 crossref_primary_10_1002__SICI_1097_0258_20000229_19_4_617__AID_SIM360_3_0_CO_2_R wiley_primary_10_1002_SICI_1097_0258_20000229_19_4_617_AID_SIM360_3_0_CO_2_R_SIM360 istex_primary_ark_67375_WNG_PF7G2648_8 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 29 February 2000 |
| PublicationDateYYYYMMDD | 2000-02-29 |
| PublicationDate_xml | – month: 02 year: 2000 text: 29 February 2000 day: 29 |
| PublicationDecade | 2000 |
| PublicationPlace | Chichester, UK |
| PublicationPlace_xml | – name: Chichester, UK – name: Elmont, NY – name: Chichester – name: England |
| PublicationTitle | Statistics in medicine |
| PublicationTitleAlternate | Statist. Med |
| PublicationYear | 2000 |
| Publisher | John Wiley & Sons, Ltd Wiley |
| Publisher_xml | – name: John Wiley & Sons, Ltd – name: Wiley |
| References | Prentice RL, Kalbfleisch JD, Peterson AV, Flournoy N, Farewell VT, Breslow NE. The analysis of failure times in the presence of competing risks. Biometrics 1978; 34:541-554. Jewell NP, Nielsen JP. A framework for consistent prediction rules based on markers. Biometrika 1993; 80:153-164. Slate EH, Clark LC. Using PSA to detect prostate cancer onset: an application of Bayesian retrospective and prospective changepoint identification. Case Studies in Bayesian Statistics IV 1998; 511-534. Clark LC, Combs GF, Turnbull BW, Slate EH, Chalker DK, Chow J, Davis LS, Glover RA, Graham GF, Gross EG, Krongrad A, Lesher JL, Park HK, Sanders BB, Smith CL, Taylor JR and the Nutritional Prevention of Cancer Study Group. Effects of selenium supplementation for cancer prevention in patients with carcinoma of the skin: A randomized clinical trial. Journal of the American Medical Association 1996; 276(24): 1957-1963. Lange N, Carlin BP, Gelfand AE. Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4 T-cell numbers (with discussion). Journal of the American Statistical Association 1992; 87:615-632. Wu MC, Carroll RJ. Estimation and comparison of changes in the presence of informative right censoring: modeling the censoring process. Biometrics 1988; 44:175-188. Oesterling JE, Jacobsen SJ, Chute CG, Guess HA, Girman CJ, Panser LA, Lieber MM. Serum prostate-specific antigen in a community-based population of healthy men. Journal of the American Medical Association 1993; 270(5):660-664. Tsiatis AA, De Gruttola V, Wulfsohn M. Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS. Journal of the American Statistical Association 1995; 90:27-37. MacDonald IL, Zucchini W. Hidden Markov and Other Models for Discrete-Valued Time Series. Chapman and Hall: New York, 1997. Stephens DA. Bayesian retrospective multiple-changepoint identification. Applied Statistics 1994; 43:159-178. Schluchter MD. Methods for the analysis of informatively censored longitudinal data. Statistics in Medicine 1992; 11:1861-1870. Page ES. A test for a change in a parameter occurring at an unknown point. Biometrika 1955; 42:523-527. Gail MH. Evaluating serial cancer marker studies in patients at risk of recurrent disease. Biometrics 1981; 37:927-936 (correction: 42, 229). Shi M, Taylor JMG, Munoz A. Models for residual time to AIDS. Lifetime Data Analysis 1996; 2:31-49. De Gruttola V, Tu XM. Modelling progression of CD4-lymphocyte count and its relationship to survival time. Biometrics 1994; 50:1003-1014. Tanner MA. Tools for Statistical Inference: Methods for the Exploration of Posterior Distribution and Likelihood Functions, 2nd edn, Springer-Verlag: New York, 1993. Morrell CH, Pearson JD, Carter HB, Brant LJ. Estimating unknown transition times using a piecewise nonlinear mixed-effects model in men with prostate cancer. Journal of the American Statistical Association 1995; 90:45-53. Orchard T, Woodbury MA. A missing information principle: theory and applications. Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics 1972; 1:697-715. Hinkley DV. Inference about the intersection in two-phase regression. Biometrika 1969; 56:495-504. Taylor JMG, Cumberland WG, Sy JP. A stochastic model for analysis of longitudinal AIDS data. Journal of the American Statistical Association 1994; 89:727-736. Day R, Bryant J, Lefkopoulou M. Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators. Biometrika 1997; 84:45-56. McLaughlin PW, Sandler HM, Jiroutek MR. Prostate-specific antigen following prostate radiotherapy: how low can you go?Journal of Clinical Oncology 1996; 14(11):2889-2892. Lindstrom MJ, Bates DM. Nonlinear mixed effects models for repeated measures data. Biometrics 1990; 46:673-687. Pawitan Y, Self S. Modeling disease marker processes in AIDS. Journal of the American Statistical Association 1993; 88:719-726. Tate H. A Bayesian approach to the analysis of serial tumour-marker data. Statistician 1983; 32:116. Carter HB, Pearson JD, Metter EJ, Brant LJ, Chan DW, Andres R, Fozard JL, Walsh PC. Longitudinal evaluation of prostate-specific antigen levels in men with and without prostate disease. Journal of the American Medical Association 1992; 267(16):2215-2220. Lindstrom MJ, Bates DM. Newton-Raphson and EM algorithm for linear mixed-effects models for repeated-measures data. Journal of the American Statistical Association 1988; 83:1014-1022. Press SJ. Applied Multivariate Analysis: Using Bayesian and Frequentist Methods of Inference. Robert E. Krieger Publishing: New York, 1982. Myers LE, Paulson DF, Berry WR, Cox EB, Laszlo J, Stanley W. A time-dependent statistical model which relates current clinical states to prognosis: application to advanced prostatic cancer. Journal of Chronic Diseases 1980; 33:491-499. Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics 1982; 38:963-974. Geman S, Geman D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence 1984; 6:721-741. Hinkley DV. Inference about the change-point in a sequence of random variables. Biometrika 1970; 57:1-17. Cleveland WS, Devlin SJ. Locally-weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association 1988; 83:596-610. Gelfand AE, Smith AFM. Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association 1990; 85:398-409. Hsieh FY, Crowley J, Tormey DC. Some test statistics for use in multistate survival analysis. Biometrika 1983; 70:111-119. Smith AFM. A Bayesian approach to inference about a change-point in a sequence of random variables. Biometrika 1975; 62:407-416. Jewell NP, Kalbfleisch JD. Marker processes in survival analysis. Lifetime Data Analysis 1996; 2:15-29. Hogan JW, Laird NM. Mixture models for the joint distribution of repeated measures and event times. Statistics in Medicine 1997; 16:239-257. Kay R. A Markov model for analysing cancer markers and disease states in survival studies. Biometrics 1986; 42:855-865. Pearson JD, Morrell CH, Landis PK, Carter HB, Brant LJ. Mixed-effects regression models for studying the natural history of prostate disease. Statistics in Medicine 1994; 13:587-601. Carlin BP, Gelfand AE, Smith AFM. Hierarchical Bayesian analysis of changepoint problems. Applied Statistics 1992; 41:389-405. Lin DY, Fleming TR, De Gruttola V. Estimating proportion of treatment effect explained by a surrogate marker. Statistics in Medicine 1997; 16:1515-1527. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Association Series B 1977; 39:1-22. Emir B, Wieand S, Su JQ, Cha S, Analysis of repeated markers used to predict progression of cancer, Statistics in Medicine 1998; 17:2563-2578. Gulyas SW, Slate EH, Turnbull BW. Fitting latent changepoint models for serial biomarkers using the EM algorithm. Computing Science and Statistics 1997; 29:253-258. Kalbfleisch JD, Prentice RL. The Statistical Analysis of Failure Time Data. Wiley: New York, 1980. Catalona WJ, Smith DS, Ratliff TL, Dodds KM, Coplen DE, Yuan JJ, Petros JA, Andriole GL. Measurement of prostate-specific antigen in serum as a screening test for prostate cancer. New England Journal of Medicine 1991; 324(17):1156-1161. Meng XL, Rubin DB. Using EM to obtain asymptotic variance-covariance matrices. Journal of the American Statistical Association 1991; 86:899-909. Satten GA, Longini IA. Markov chains with measurement error: estimating the 'true' course of a marker of the preogression of human immunodeficiency virus disease (with discussion). Applied Statistics 1996; 45:275-309. Whittemore AS, Lele C, Friedman GC, Stamey T, Vogelman JJ, Orentreich N. Prostate-specific antigen as predictor of prostate cancer in black men and white men. Journal of the National Cancer Institute 1995; 87(5): 354-360. Gulyas SW, Slate EH, Turnbull BW. Latent changepoint process models for longitudinal biomarkers of disease. Proceedings of the Biometrics Section 1997; 249-252. Louis TA. Finding observed information using the EM algorithm. Journal of the Royal Statistical Society Series B 1982; 44:98-130. Carter HB, Epstein JI, Chan DW, Fozard JL, Pearson JD. Recommended prostate-specific antigen testing intervals for the detection of cureable prostate cancer. Journal of the American Medical Association 1997; 277(18):1456-1460. Murtaugh PA. ROC curves with multiple marker measurements. Biometrics 1995; 51:1514-1522. Catalona WJ, Smith DS, Ratliff TL, Basler JW. Detection of organ-confined prostate cancer is increased through prostate-specific antigen-based screening. Journal of the American Medical Association 1993; 270(8):948-954. Cronin KA, Slate EH, Turnbull BW, Wells MT. Using the Gibbs sampler to detect changepoints: application to PSA as a longitudinal marker for prostate cancer. Computing Science and Statistics 1994; 26:314-318. Hogan JW, Laird NM. Model-based approaches to analysing incomplete longitudinal and failure time data. Statistics in Medicine 1997; 16:259-272. Klein JP, Klotz JH, Grever MR. A biological marker model for predicting disease transitions. Biometrics 1984; 40:927-936. Seber GAF, Wild CJ. Nonlinear Regression. Wiley: New York, 1989. 1997; 84 1978; 34 1997; 277 1994; 26 1955; 42 1992; 11 1990; 85 1998; 17 1990; 46 1986; 42 1977; 39 1991; 86 1980; 33 1988; 44 1981; 37 1997; 16 1993; 80 1988; 83 1982 1980 1992; 87 1996; 2 1989 1992; 41 1984; 40 1995; 51 1982; 38 1995; 90 1993; 88 1992; 267 1994; 89 1969; 56 1998 1983; 32 1997 1997; 29 1995 1993 1983; 70 1996; 14 1972; 1 1994; 43 1970; 57 1984; 6 1995; 87 1982; 44 1993; 270 1994; 13 1996; 276 1994; 50 1975; 62 1991; 324 1996; 45 Lindstrom (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB43|cit43) 1988; 83 Gelfand (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB52|cit52) 1990; 85 Page (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB26|cit26) 1955; 42 Pearson (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB38|cit38) 1994; 13 Schluchter (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB12|cit12) 1992; 11 Laird (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB16|cit16) 1982; 38 Hogan (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB13|cit13) 1997; 16 Lin (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB6|cit6) 1997; 16 Lindstrom (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB44|cit44) 1990; 46 Morrell (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB46|cit46) 1995; 90 Carter (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB2|cit2) 1992; 267 Clark (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB39|cit39) 1996; 276 Catalona (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB33|cit33) 1991; 324 Whittemore (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB36|cit36) 1995; 87 Klein (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB21|cit21) 1984; 40 MacDonald (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB32|cit32) 1997 Slate (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB42|cit42) 1997 Hsieh (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB22|cit22) 1983; 70 Kay (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB24|cit24) 1986; 42 Satten (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB25|cit25) 1996; 45 Hinkley (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB28|cit28) 1970; 57 Cleveland (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB40|cit40) 1988; 83 Jewell (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB8|cit8) 1993; 80 Tate (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB1|cit1) 1983; 32 Slate (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB49|cit49) 1998 Shi (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB19|cit19) 1996; 2 Smith (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB29|cit29) 1975; 62 Meng (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB61|cit61) 1991; 86 Stephens (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB31|cit31) 1994; 43 Dempster (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB58|cit58) 1977; 39 McLaughlin (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB41|cit41) 1996; 14 Myers (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB23|cit23) 1980; 33 Prentice (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB4|cit4) 1978; 34 Emir (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB54|cit54) 1998; 17 Murtaugh (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB55|cit55) 1995; 51 Gulyas (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB57|cit57) 1997 Gail (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB5|cit5) 1981; 37 Tsiatis (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB9|cit9) 1995; 90 Lange (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB47|cit47) 1992; 87 Tanner (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB62|cit62) 1993 Carlin (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB30|cit30) 1992; 41 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB35|cit35 Catalona (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB34|cit34) 1993; 270 Geman (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB51|cit51) 1984; 6 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB53|cit53 Jewell (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB18|cit18) 1996; 2 Oesterling (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB37|cit37) 1993; 270 Hogan (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB14|cit14) 1997; 16 Carter (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB3|cit3) 1997; 277 Pawitan (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB15|cit15) 1993; 88 Louis (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB60|cit60) 1982; 44 Seber (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB45|cit45) 1989 Orchard (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB59|cit59) 1972; 1 Taylor (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB17|cit17) 1994; 89 Kalbfleisch (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB7|cit7) 1980 Day (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB20|cit20) 1997; 84 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB63|cit63 Gulyas (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB56|cit56) 1997; 29 De Gruttola (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB10|cit10) 1994; 50 Press (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB50|cit50) 1982 Cronin (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB48|cit48) 1994; 26 Hinkley (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB27|cit27) 1969; 56 Wu (10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB11|cit11) 1988; 44 |
| References_xml | – reference: MacDonald IL, Zucchini W. Hidden Markov and Other Models for Discrete-Valued Time Series. Chapman and Hall: New York, 1997. – reference: Hsieh FY, Crowley J, Tormey DC. Some test statistics for use in multistate survival analysis. Biometrika 1983; 70:111-119. – reference: Lindstrom MJ, Bates DM. Newton-Raphson and EM algorithm for linear mixed-effects models for repeated-measures data. Journal of the American Statistical Association 1988; 83:1014-1022. – reference: Cleveland WS, Devlin SJ. Locally-weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association 1988; 83:596-610. – reference: Hogan JW, Laird NM. Model-based approaches to analysing incomplete longitudinal and failure time data. Statistics in Medicine 1997; 16:259-272. – reference: Murtaugh PA. ROC curves with multiple marker measurements. Biometrics 1995; 51:1514-1522. – reference: Day R, Bryant J, Lefkopoulou M. Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators. Biometrika 1997; 84:45-56. – reference: Gelfand AE, Smith AFM. Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association 1990; 85:398-409. – reference: Gulyas SW, Slate EH, Turnbull BW. Latent changepoint process models for longitudinal biomarkers of disease. Proceedings of the Biometrics Section 1997; 249-252. – reference: Hinkley DV. Inference about the intersection in two-phase regression. Biometrika 1969; 56:495-504. – reference: Satten GA, Longini IA. Markov chains with measurement error: estimating the 'true' course of a marker of the preogression of human immunodeficiency virus disease (with discussion). Applied Statistics 1996; 45:275-309. – reference: Myers LE, Paulson DF, Berry WR, Cox EB, Laszlo J, Stanley W. A time-dependent statistical model which relates current clinical states to prognosis: application to advanced prostatic cancer. Journal of Chronic Diseases 1980; 33:491-499. – reference: Tanner MA. Tools for Statistical Inference: Methods for the Exploration of Posterior Distribution and Likelihood Functions, 2nd edn, Springer-Verlag: New York, 1993. – reference: Cronin KA, Slate EH, Turnbull BW, Wells MT. Using the Gibbs sampler to detect changepoints: application to PSA as a longitudinal marker for prostate cancer. Computing Science and Statistics 1994; 26:314-318. – reference: Taylor JMG, Cumberland WG, Sy JP. A stochastic model for analysis of longitudinal AIDS data. Journal of the American Statistical Association 1994; 89:727-736. – reference: Prentice RL, Kalbfleisch JD, Peterson AV, Flournoy N, Farewell VT, Breslow NE. The analysis of failure times in the presence of competing risks. Biometrics 1978; 34:541-554. – reference: De Gruttola V, Tu XM. Modelling progression of CD4-lymphocyte count and its relationship to survival time. Biometrics 1994; 50:1003-1014. – reference: Smith AFM. A Bayesian approach to inference about a change-point in a sequence of random variables. Biometrika 1975; 62:407-416. – reference: Whittemore AS, Lele C, Friedman GC, Stamey T, Vogelman JJ, Orentreich N. Prostate-specific antigen as predictor of prostate cancer in black men and white men. Journal of the National Cancer Institute 1995; 87(5): 354-360. – reference: Orchard T, Woodbury MA. A missing information principle: theory and applications. Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics 1972; 1:697-715. – reference: Kay R. A Markov model for analysing cancer markers and disease states in survival studies. Biometrics 1986; 42:855-865. – reference: Jewell NP, Nielsen JP. A framework for consistent prediction rules based on markers. Biometrika 1993; 80:153-164. – reference: Oesterling JE, Jacobsen SJ, Chute CG, Guess HA, Girman CJ, Panser LA, Lieber MM. Serum prostate-specific antigen in a community-based population of healthy men. Journal of the American Medical Association 1993; 270(5):660-664. – reference: Pawitan Y, Self S. Modeling disease marker processes in AIDS. Journal of the American Statistical Association 1993; 88:719-726. – reference: Press SJ. Applied Multivariate Analysis: Using Bayesian and Frequentist Methods of Inference. Robert E. Krieger Publishing: New York, 1982. – reference: Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics 1982; 38:963-974. – reference: Carlin BP, Gelfand AE, Smith AFM. Hierarchical Bayesian analysis of changepoint problems. Applied Statistics 1992; 41:389-405. – reference: Lange N, Carlin BP, Gelfand AE. Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4 T-cell numbers (with discussion). Journal of the American Statistical Association 1992; 87:615-632. – reference: Pearson JD, Morrell CH, Landis PK, Carter HB, Brant LJ. Mixed-effects regression models for studying the natural history of prostate disease. Statistics in Medicine 1994; 13:587-601. – reference: Hogan JW, Laird NM. Mixture models for the joint distribution of repeated measures and event times. Statistics in Medicine 1997; 16:239-257. – reference: Hinkley DV. Inference about the change-point in a sequence of random variables. Biometrika 1970; 57:1-17. – reference: McLaughlin PW, Sandler HM, Jiroutek MR. Prostate-specific antigen following prostate radiotherapy: how low can you go?Journal of Clinical Oncology 1996; 14(11):2889-2892. – reference: Morrell CH, Pearson JD, Carter HB, Brant LJ. Estimating unknown transition times using a piecewise nonlinear mixed-effects model in men with prostate cancer. Journal of the American Statistical Association 1995; 90:45-53. – reference: Jewell NP, Kalbfleisch JD. Marker processes in survival analysis. Lifetime Data Analysis 1996; 2:15-29. – reference: Carter HB, Epstein JI, Chan DW, Fozard JL, Pearson JD. Recommended prostate-specific antigen testing intervals for the detection of cureable prostate cancer. Journal of the American Medical Association 1997; 277(18):1456-1460. – reference: Schluchter MD. Methods for the analysis of informatively censored longitudinal data. Statistics in Medicine 1992; 11:1861-1870. – reference: Lin DY, Fleming TR, De Gruttola V. Estimating proportion of treatment effect explained by a surrogate marker. Statistics in Medicine 1997; 16:1515-1527. – reference: Shi M, Taylor JMG, Munoz A. Models for residual time to AIDS. Lifetime Data Analysis 1996; 2:31-49. – reference: Geman S, Geman D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence 1984; 6:721-741. – reference: Gail MH. Evaluating serial cancer marker studies in patients at risk of recurrent disease. Biometrics 1981; 37:927-936 (correction: 42, 229). – reference: Clark LC, Combs GF, Turnbull BW, Slate EH, Chalker DK, Chow J, Davis LS, Glover RA, Graham GF, Gross EG, Krongrad A, Lesher JL, Park HK, Sanders BB, Smith CL, Taylor JR and the Nutritional Prevention of Cancer Study Group. Effects of selenium supplementation for cancer prevention in patients with carcinoma of the skin: A randomized clinical trial. Journal of the American Medical Association 1996; 276(24): 1957-1963. – reference: Tate H. A Bayesian approach to the analysis of serial tumour-marker data. Statistician 1983; 32:116. – reference: Meng XL, Rubin DB. Using EM to obtain asymptotic variance-covariance matrices. Journal of the American Statistical Association 1991; 86:899-909. – reference: Carter HB, Pearson JD, Metter EJ, Brant LJ, Chan DW, Andres R, Fozard JL, Walsh PC. Longitudinal evaluation of prostate-specific antigen levels in men with and without prostate disease. Journal of the American Medical Association 1992; 267(16):2215-2220. – reference: Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Association Series B 1977; 39:1-22. – reference: Page ES. A test for a change in a parameter occurring at an unknown point. Biometrika 1955; 42:523-527. – reference: Catalona WJ, Smith DS, Ratliff TL, Dodds KM, Coplen DE, Yuan JJ, Petros JA, Andriole GL. Measurement of prostate-specific antigen in serum as a screening test for prostate cancer. New England Journal of Medicine 1991; 324(17):1156-1161. – reference: Catalona WJ, Smith DS, Ratliff TL, Basler JW. Detection of organ-confined prostate cancer is increased through prostate-specific antigen-based screening. Journal of the American Medical Association 1993; 270(8):948-954. – reference: Emir B, Wieand S, Su JQ, Cha S, Analysis of repeated markers used to predict progression of cancer, Statistics in Medicine 1998; 17:2563-2578. – reference: Slate EH, Clark LC. Using PSA to detect prostate cancer onset: an application of Bayesian retrospective and prospective changepoint identification. Case Studies in Bayesian Statistics IV 1998; 511-534. – reference: Tsiatis AA, De Gruttola V, Wulfsohn M. Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS. Journal of the American Statistical Association 1995; 90:27-37. – reference: Wu MC, Carroll RJ. Estimation and comparison of changes in the presence of informative right censoring: modeling the censoring process. Biometrics 1988; 44:175-188. – reference: Seber GAF, Wild CJ. Nonlinear Regression. Wiley: New York, 1989. – reference: Gulyas SW, Slate EH, Turnbull BW. Fitting latent changepoint models for serial biomarkers using the EM algorithm. Computing Science and Statistics 1997; 29:253-258. – reference: Klein JP, Klotz JH, Grever MR. A biological marker model for predicting disease transitions. Biometrics 1984; 40:927-936. – reference: Stephens DA. Bayesian retrospective multiple-changepoint identification. Applied Statistics 1994; 43:159-178. – reference: Louis TA. Finding observed information using the EM algorithm. Journal of the Royal Statistical Society Series B 1982; 44:98-130. – reference: Kalbfleisch JD, Prentice RL. The Statistical Analysis of Failure Time Data. Wiley: New York, 1980. – reference: Lindstrom MJ, Bates DM. Nonlinear mixed effects models for repeated measures data. Biometrics 1990; 46:673-687. – volume: 42 start-page: 855 year: 1986 end-page: 865 article-title: A Markov model for analysing cancer markers and disease states in survival studies publication-title: Biometrics – volume: 276 start-page: 1957 issue: 24 year: 1996 end-page: 1963 article-title: Effects of selenium supplementation for cancer prevention in patients with carcinoma of the skin: A randomized clinical trial publication-title: Journal of the American Medical Association – volume: 46 start-page: 673 year: 1990 end-page: 687 article-title: Nonlinear mixed effects models for repeated measures data publication-title: Biometrics – volume: 85 start-page: 398 year: 1990 end-page: 409 article-title: Sampling‐based approaches to calculating marginal densities publication-title: Journal of the American Statistical Association – volume: 11 start-page: 1861 year: 1992 end-page: 1870 article-title: Methods for the analysis of informatively censored longitudinal data publication-title: Statistics in Medicine – volume: 16 start-page: 259 year: 1997 end-page: 272 article-title: Model‐based approaches to analysing incomplete longitudinal and failure time data publication-title: Statistics in Medicine – volume: 277 start-page: 1456 issue: 18 year: 1997 end-page: 1460 article-title: Recommended prostate‐specific antigen testing intervals for the detection of cureable prostate cancer publication-title: Journal of the American Medical Association – volume: 16 start-page: 239 year: 1997 end-page: 257 article-title: Mixture models for the joint distribution of repeated measures and event times publication-title: Statistics in Medicine – year: 1989 – volume: 17 start-page: 2563 year: 1998 end-page: 2578 article-title: Analysis of repeated markers used to predict progression of cancer publication-title: Statistics in Medicine – volume: 50 start-page: 1003 year: 1994 end-page: 1014 article-title: Modelling progression of CD4‐lymphocyte count and its relationship to survival time publication-title: Biometrics – volume: 62 start-page: 407 year: 1975 end-page: 416 article-title: A Bayesian approach to inference about a change‐point in a sequence of random variables publication-title: Biometrika – volume: 13 start-page: 587 year: 1994 end-page: 601 article-title: Mixed‐effects regression models for studying the natural history of prostate disease publication-title: Statistics in Medicine – volume: 267 start-page: 2215 issue: 16 year: 1992 end-page: 2220 article-title: Longitudinal evaluation of prostate‐specific antigen levels in men with and without prostate disease publication-title: Journal of the American Medical Association – volume: 16 start-page: 1515 year: 1997 end-page: 1527 article-title: Estimating proportion of treatment effect explained by a surrogate marker publication-title: Statistics in Medicine – volume: 56 start-page: 495 year: 1969 end-page: 504 article-title: Inference about the intersection in two‐phase regression publication-title: Biometrika – year: 1998 – volume: 37 start-page: 927 year: 1981 end-page: 936 article-title: Evaluating serial cancer marker studies in patients at risk of recurrent disease publication-title: Biometrics – volume: 39 start-page: 1 year: 1977 end-page: 22 article-title: Maximum likelihood from incomplete data via the EM algorithm publication-title: Journal of the Royal Statistical Association Series B – volume: 89 start-page: 727 year: 1994 end-page: 736 article-title: A stochastic model for analysis of longitudinal AIDS data publication-title: Journal of the American Statistical Association – year: 1982 – volume: 45 start-page: 275 year: 1996 end-page: 309 article-title: Markov chains with measurement error: estimating the ‘true’ course of a marker of the preogression of human immunodeficiency virus disease (with discussion) publication-title: Applied Statistics – volume: 2 start-page: 15 year: 1996 end-page: 29 article-title: Marker processes in survival analysis publication-title: Lifetime Data Analysis – year: 1997 – start-page: 511 year: 1998 end-page: 534 article-title: Using PSA to detect prostate cancer onset: an application of Bayesian retrospective and prospective changepoint identification publication-title: Case Studies in Bayesian Statistics IV – volume: 42 start-page: 523 year: 1955 end-page: 527 article-title: A test for a change in a parameter occurring at an unknown point publication-title: Biometrika – volume: 87 start-page: 615 year: 1992 end-page: 632 article-title: Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4 T‐cell numbers (with discussion) publication-title: Journal of the American Statistical Association – start-page: 249 year: 1997 end-page: 252 article-title: Latent changepoint process models for longitudinal biomarkers of disease publication-title: Proceedings of the Biometrics Section – volume: 324 start-page: 1156 issue: 17 year: 1991 end-page: 1161 article-title: Measurement of prostate‐specific antigen in serum as a screening test for prostate cancer publication-title: New England Journal of Medicine – year: 1993 – volume: 44 start-page: 98 year: 1982 end-page: 130 article-title: Finding observed information using the EM algorithm publication-title: Journal of the Royal Statistical Society Series B – volume: 6 start-page: 721 year: 1984 end-page: 741 article-title: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – volume: 32 start-page: 116 year: 1983 article-title: A Bayesian approach to the analysis of serial tumour‐marker data publication-title: Statistician – volume: 70 start-page: 111 year: 1983 end-page: 119 article-title: Some test statistics for use in multistate survival analysis publication-title: Biometrika – volume: 29 start-page: 253 year: 1997 end-page: 258 article-title: Fitting latent changepoint models for serial biomarkers using the EM algorithm publication-title: Computing Science and Statistics – volume: 33 start-page: 491 year: 1980 end-page: 499 article-title: A time‐dependent statistical model which relates current clinical states to prognosis: application to advanced prostatic cancer publication-title: Journal of Chronic Diseases – volume: 38 start-page: 963 year: 1982 end-page: 974 article-title: Random‐effects models for longitudinal data publication-title: Biometrics – volume: 34 start-page: 541 year: 1978 end-page: 554 article-title: The analysis of failure times in the presence of competing risks publication-title: Biometrics – volume: 26 start-page: 314 year: 1994 end-page: 318 article-title: Using the Gibbs sampler to detect changepoints: application to PSA as a longitudinal marker for prostate cancer publication-title: Computing Science and Statistics – volume: 87 start-page: 354 issue: 5 year: 1995 end-page: 360 article-title: Prostate‐specific antigen as predictor of prostate cancer in black men and white men publication-title: Journal of the National Cancer Institute – volume: 90 start-page: 27 year: 1995 end-page: 37 article-title: Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS publication-title: Journal of the American Statistical Association – volume: 14 start-page: 2889 issue: 11 year: 1996 end-page: 2892 article-title: Prostate‐specific antigen following prostate radiotherapy: how low can you go? publication-title: Journal of Clinical Oncology – volume: 41 start-page: 389 year: 1992 end-page: 405 article-title: Hierarchical Bayesian analysis of changepoint problems publication-title: Applied Statistics – volume: 51 start-page: 1514 year: 1995 end-page: 1522 article-title: ROC curves with multiple marker measurements publication-title: Biometrics – volume: 40 start-page: 927 year: 1984 end-page: 936 article-title: A biological marker model for predicting disease transitions publication-title: Biometrics – volume: 88 start-page: 719 year: 1993 end-page: 726 article-title: Modeling disease marker processes in AIDS publication-title: Journal of the American Statistical Association – volume: 1 start-page: 697 year: 1972 end-page: 715 article-title: A missing information principle: theory and applications publication-title: Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics – volume: 90 start-page: 45 year: 1995 end-page: 53 article-title: Estimating unknown transition times using a piecewise nonlinear mixed‐effects model in men with prostate cancer publication-title: Journal of the American Statistical Association – volume: 83 start-page: 1014 year: 1988 end-page: 1022 article-title: Newton‐Raphson and EM algorithm for linear mixed‐effects models for repeated‐measures data publication-title: Journal of the American Statistical Association – volume: 2 start-page: 31 year: 1996 end-page: 49 article-title: Models for residual time to AIDS publication-title: Lifetime Data Analysis – volume: 57 start-page: 1 year: 1970 end-page: 17 article-title: Inference about the change‐point in a sequence of random variables publication-title: Biometrika – volume: 80 start-page: 153 year: 1993 end-page: 164 article-title: A framework for consistent prediction rules based on markers publication-title: Biometrika – start-page: 444 year: 1997 end-page: 456 – volume: 44 start-page: 175 year: 1988 end-page: 188 article-title: Estimation and comparison of changes in the presence of informative right censoring: modeling the censoring process publication-title: Biometrics – year: 1980 – volume: 270 start-page: 948 issue: 8 year: 1993 end-page: 954 article-title: Detection of organ‐confined prostate cancer is increased through prostate‐specific antigen‐based screening publication-title: Journal of the American Medical Association – volume: 83 start-page: 596 year: 1988 end-page: 610 article-title: Locally‐weighted regression: an approach to regression analysis by local fitting publication-title: Journal of the American Statistical Association – year: 1995 – volume: 84 start-page: 45 year: 1997 end-page: 56 article-title: Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators publication-title: Biometrika – volume: 86 start-page: 899 year: 1991 end-page: 909 article-title: Using EM to obtain asymptotic variance‐covariance matrices publication-title: Journal of the American Statistical Association – volume: 270 start-page: 660 issue: 5 year: 1993 end-page: 664 article-title: Serum prostate‐specific antigen in a community‐based population of healthy men publication-title: Journal of the American Medical Association – volume: 43 start-page: 159 year: 1994 end-page: 178 article-title: Bayesian retrospective multiple‐changepoint identification publication-title: Applied Statistics – volume: 44 start-page: 98 year: 1982 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB60|cit60 article-title: Finding observed information using the EM algorithm publication-title: Journal of the Royal Statistical Society Series B doi: 10.1111/j.2517-6161.1982.tb01203.x – volume: 83 start-page: 1014 year: 1988 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB43|cit43 article-title: Newton-Raphson and EM algorithm for linear mixed-effects models for repeated-measures data publication-title: Journal of the American Statistical Association – ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB63|cit63 – volume: 6 start-page: 721 year: 1984 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB51|cit51 article-title: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.1984.4767596 – volume: 43 start-page: 159 year: 1994 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB31|cit31 article-title: Bayesian retrospective multiple-changepoint identification publication-title: Applied Statistics doi: 10.2307/2986119 – volume: 34 start-page: 541 year: 1978 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB4|cit4 article-title: The analysis of failure times in the presence of competing risks publication-title: Biometrics doi: 10.2307/2530374 – volume: 16 start-page: 239 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB13|cit13 article-title: Mixture models for the joint distribution of repeated measures and event times publication-title: Statistics in Medicine doi: 10.1002/(SICI)1097-0258(19970215)16:3<239::AID-SIM483>3.0.CO;2-X – volume: 2 start-page: 15 year: 1996 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB18|cit18 article-title: Marker processes in survival analysis publication-title: Lifetime Data Analysis doi: 10.1007/BF00128468 – volume: 42 start-page: 855 year: 1986 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB24|cit24 article-title: A Markov model for analysing cancer markers and disease states in survival studies publication-title: Biometrics doi: 10.2307/2530699 – volume: 29 start-page: 253 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB56|cit56 article-title: Fitting latent changepoint models for serial biomarkers using the EM algorithm publication-title: Computing Science and Statistics – volume: 16 start-page: 259 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB14|cit14 article-title: Model-based approaches to analysing incomplete longitudinal and failure time data publication-title: Statistics in Medicine doi: 10.1002/(SICI)1097-0258(19970215)16:3<259::AID-SIM484>3.0.CO;2-S – volume-title: Nonlinear Regression year: 1989 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB45|cit45 doi: 10.1002/0471725315 – volume-title: Applied Multivariate Analysis: Using Bayesian and Frequentist Methods of Inference year: 1982 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB50|cit50 – volume: 38 start-page: 963 year: 1982 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB16|cit16 article-title: Random-effects models for longitudinal data publication-title: Biometrics doi: 10.2307/2529876 – volume: 41 start-page: 389 year: 1992 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB30|cit30 article-title: Hierarchical Bayesian analysis of changepoint problems publication-title: Applied Statistics doi: 10.2307/2347570 – volume: 324 start-page: 1156 issue: 17 year: 1991 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB33|cit33 article-title: Measurement of prostate-specific antigen in serum as a screening test for prostate cancer publication-title: New England Journal of Medicine doi: 10.1056/NEJM199104253241702 – volume: 87 start-page: 354 issue: 5 year: 1995 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB36|cit36 article-title: Prostate-specific antigen as predictor of prostate cancer in black men and white men publication-title: Journal of the National Cancer Institute doi: 10.1093/jnci/87.5.354 – volume-title: The Statistical Analysis of Failure Time Data year: 1980 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB7|cit7 – volume: 84 start-page: 45 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB20|cit20 article-title: Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators publication-title: Biometrika doi: 10.1093/biomet/84.1.45 – ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB53|cit53 – volume: 89 start-page: 727 year: 1994 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB17|cit17 article-title: A stochastic model for analysis of longitudinal AIDS data publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1994.10476806 – volume: 33 start-page: 491 year: 1980 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB23|cit23 article-title: A time-dependent statistical model which relates current clinical states to prognosis: application to advanced prostatic cancer publication-title: Journal of Chronic Diseases doi: 10.1016/0021-9681(80)90074-0 – volume: 62 start-page: 407 year: 1975 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB29|cit29 article-title: A Bayesian approach to inference about a change-point in a sequence of random variables publication-title: Biometrika doi: 10.1093/biomet/62.2.407 – volume: 70 start-page: 111 year: 1983 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB22|cit22 article-title: Some test statistics for use in multistate survival analysis publication-title: Biometrika doi: 10.1093/biomet/70.1.111 – volume: 1 start-page: 697 year: 1972 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB59|cit59 article-title: A missing information principle: theory and applications publication-title: Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics – volume-title: Tools for Statistical Inference: Methods for the Exploration of Posterior Distribution and Likelihood Functions year: 1993 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB62|cit62 doi: 10.1007/978-1-4684-0192-9 – volume: 277 start-page: 1456 issue: 18 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB3|cit3 article-title: Recommended prostate-specific antigen testing intervals for the detection of cureable prostate cancer publication-title: Journal of the American Medical Association doi: 10.1001/jama.1997.03540420052029 – volume: 13 start-page: 587 year: 1994 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB38|cit38 article-title: Mixed-effects regression models for studying the natural history of prostate disease publication-title: Statistics in Medicine doi: 10.1002/sim.4780130520 – volume: 88 start-page: 719 year: 1993 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB15|cit15 article-title: Modeling disease marker processes in AIDS publication-title: Journal of the American Statistical Association – volume: 42 start-page: 523 year: 1955 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB26|cit26 article-title: A test for a change in a parameter occurring at an unknown point publication-title: Biometrika doi: 10.1093/biomet/42.3-4.523 – volume: 11 start-page: 1861 year: 1992 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB12|cit12 article-title: Methods for the analysis of informatively censored longitudinal data publication-title: Statistics in Medicine doi: 10.1002/sim.4780111408 – volume: 46 start-page: 673 year: 1990 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB44|cit44 article-title: Nonlinear mixed effects models for repeated measures data publication-title: Biometrics doi: 10.2307/2532087 – volume: 57 start-page: 1 year: 1970 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB28|cit28 article-title: Inference about the change-point in a sequence of random variables publication-title: Biometrika doi: 10.1093/biomet/57.1.1 – volume: 276 start-page: 1957 issue: 24 year: 1996 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB39|cit39 article-title: Effects of selenium supplementation for cancer prevention in patients with carcinoma of the skin: A randomized clinical trial publication-title: Journal of the American Medical Association doi: 10.1001/jama.1996.03540240035027 – volume: 56 start-page: 495 year: 1969 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB27|cit27 article-title: Inference about the intersection in two-phase regression publication-title: Biometrika doi: 10.1093/biomet/56.3.495 – volume: 50 start-page: 1003 year: 1994 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB10|cit10 article-title: Modelling progression of CD4-lymphocyte count and its relationship to survival time publication-title: Biometrics doi: 10.2307/2533439 – volume: 270 start-page: 660 issue: 5 year: 1993 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB37|cit37 article-title: Serum prostate-specific antigen in a community-based population of healthy men publication-title: Journal of the American Medical Association – volume: 270 start-page: 948 issue: 8 year: 1993 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB34|cit34 article-title: Detection of organ-confined prostate cancer is increased through prostate-specific antigen-based screening publication-title: Journal of the American Medical Association doi: 10.1001/jama.1993.03510080052031 – volume: 39 start-page: 1 year: 1977 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB58|cit58 article-title: Maximum likelihood from incomplete data via the EM algorithm publication-title: Journal of the Royal Statistical Association Series B doi: 10.1111/j.2517-6161.1977.tb01600.x – volume: 80 start-page: 153 year: 1993 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB8|cit8 article-title: A framework for consistent prediction rules based on markers publication-title: Biometrika doi: 10.1093/biomet/80.1.153 – volume: 40 start-page: 927 year: 1984 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB21|cit21 article-title: A biological marker model for predicting disease transitions publication-title: Biometrics doi: 10.2307/2531144 – volume: 26 start-page: 314 year: 1994 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB48|cit48 article-title: Using the Gibbs sampler to detect changepoints: application to PSA as a longitudinal marker for prostate cancer publication-title: Computing Science and Statistics – start-page: 444 volume-title: Case Studies in Bayesian Statistics III year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB42|cit42 – start-page: 249 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB57|cit57 article-title: Latent changepoint process models for longitudinal biomarkers of disease publication-title: Proceedings of the Biometrics Section – volume: 267 start-page: 2215 issue: 16 year: 1992 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB2|cit2 article-title: Longitudinal evaluation of prostate-specific antigen levels in men with and without prostate disease publication-title: Journal of the American Medical Association doi: 10.1001/jama.1992.03480160073037 – volume-title: Hidden Markov and Other Models for Discrete-Valued Time Series year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB32|cit32 – volume: 90 start-page: 27 year: 1995 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB9|cit9 article-title: Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1995.10476485 – volume: 87 start-page: 615 year: 1992 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB47|cit47 article-title: Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4 T-cell numbers (with discussion) publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1992.10475258 – volume: 45 start-page: 275 year: 1996 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB25|cit25 article-title: Markov chains with measurement error: estimating the ‘true’ course of a marker of the preogression of human immunodeficiency virus disease (with discussion) publication-title: Applied Statistics doi: 10.2307/2986089 – volume: 2 start-page: 31 year: 1996 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB19|cit19 article-title: Models for residual time to AIDS publication-title: Lifetime Data Analysis doi: 10.1007/BF00128469 – volume: 14 start-page: 2889 issue: 11 year: 1996 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB41|cit41 article-title: Prostate-specific antigen following prostate radiotherapy: how low can you go? publication-title: Journal of Clinical Oncology doi: 10.1200/JCO.1996.14.11.2889 – volume: 86 start-page: 899 year: 1991 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB61|cit61 article-title: Using EM to obtain asymptotic variance-covariance matrices publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1991.10475130 – volume: 51 start-page: 1514 year: 1995 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB55|cit55 article-title: ROC curves with multiple marker measurements publication-title: Biometrics doi: 10.2307/2533281 – volume: 90 start-page: 45 year: 1995 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB46|cit46 article-title: Estimating unknown transition times using a piecewise nonlinear mixed-effects model in men with prostate cancer publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1995.10476487 – volume: 44 start-page: 175 year: 1988 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB11|cit11 article-title: Estimation and comparison of changes in the presence of informative right censoring: modeling the censoring process publication-title: Biometrics doi: 10.2307/2531905 – volume: 17 start-page: 2563 year: 1998 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB54|cit54 article-title: Analysis of repeated markers used to predict progression of cancer publication-title: Statistics in Medicine doi: 10.1002/(SICI)1097-0258(19981130)17:22<2563::AID-SIM952>3.0.CO;2-O – volume: 37 start-page: 927 year: 1981 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB5|cit5 article-title: Evaluating serial cancer marker studies in patients at risk of recurrent disease publication-title: Biometrics doi: 10.2307/2530523 – ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB35|cit35 – start-page: 511 year: 1998 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB49|cit49 article-title: Using PSA to detect prostate cancer onset: an application of Bayesian retrospective and prospective changepoint identification publication-title: Case Studies in Bayesian Statistics IV – volume: 16 start-page: 1515 year: 1997 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB6|cit6 article-title: Estimating proportion of treatment effect explained by a surrogate marker publication-title: Statistics in Medicine doi: 10.1002/(SICI)1097-0258(19970715)16:13<1515::AID-SIM572>3.0.CO;2-1 – volume: 32 start-page: 116 year: 1983 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB1|cit1 article-title: A Bayesian approach to the analysis of serial tumour-marker data publication-title: Statistician doi: 10.2307/2987598 – volume: 83 start-page: 596 year: 1988 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB40|cit40 article-title: Locally-weighted regression: an approach to regression analysis by local fitting publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1988.10478639 – volume: 85 start-page: 398 year: 1990 ident: 10.1002/(SICI)1097-0258(20000229)19:4<617::AID-SIM360>3.0.CO;2-R-BIB52|cit52 article-title: Sampling-based approaches to calculating marginal densities publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1990.10476213 |
| SSID | ssj0011527 |
| Score | 1.8843722 |
| Snippet | We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The... |
| SourceID | proquest pubmed pascalfrancis crossref wiley istex |
| SourceType | Aggregation Database Index Database Publisher |
| StartPage | 617 |
| SubjectTerms | Algorithms Bayes Theorem Biological and medical sciences Biomarkers Computerized, statistical medical data processing and models in biomedicine Humans Longitudinal Studies Male Medical sciences Medical statistics Models, Statistical Prostate-Specific Antigen Prostatic Neoplasms - diagnosis ROC Curve |
| Title | Statistical models for longitudinal biomarkers of disease onset |
| URI | https://api.istex.fr/ark:/67375/WNG-PF7G2648-8/fulltext.pdf https://onlinelibrary.wiley.com/doi/abs/10.1002%2F%28SICI%291097-0258%2820000229%2919%3A4%3C617%3A%3AAID-SIM360%3E3.0.CO%3B2-R https://www.ncbi.nlm.nih.gov/pubmed/10694740 https://www.proquest.com/docview/70941104 |
| Volume | 19 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwxV3db9MwELemIU2TEB_lK8AgDxRtD-mS2HHighCjW7cidYOWib2dYsd5AbVobSXEA_8K_yp3cdJSmMQTQqqq1g---Hy2fxff_Y6xZzlPrS5MHiiBvonIpAyU1DrIRGxUWEQmk5Q7PDyVJ-fi7UVyscG-N7kwjh9i-cKNVka1X9MCz_Vsf0UaigBsPOgN0GGmS9QAz-4MmyjzBI8lRc0KJ1m0eQ8PafyFn4PBYTAeDLkM2_yId8JO76zN38TBCLfwiEui3j8cLdmnoqbiK91yyjRKttjrWvz-LoneWwrebcTuRaorXqLAbncl7JUT9QIFrZ1-12giv1I0Zj7DCSldJY2roO46cq6Ovv5N9qNRmot4-dRZzHXHfPuNT_L_afUWu1Gjav_ALYPbbMNOWmxrWMcNtNh193bSd0lXLbZNGNtRVN9Bf6X5g11UlYFmPkJ5__OUajktCqob5hNNAUUyXc78aenX11o-haLP77Lz_tGH3klQ15UIDPHrB6lIjBaWK67j3MSJVWWYG43fYWl4gR6j4lJHxoioNHEoKFMxL4tM5VQ40qb8HtucTCf2AfO1KWyBBmJLYREKWV1yXUal0hZhkMxTj71v5hu-OPoQcETRMQApuo4AQDVDo2SIFAhA9QKgasGpFjiE0DuDGEYee14ZzrJDHD2F56UJfDw9hnf99JjCFiHz2M6aZa2eADdyJZXHnjaWBrip0E1RPrHTxQxSdPoRFwqP3XcG-MvDSyVSEXpsXJnRH6P666CuHFPd8vCf9PqIbTsChTiI1WO2Ob9c2B2EknP9pFrwPwGVJE7u |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwxV3db9MwED-NTRqTEB_lK8BYHijaHtIlsZvEBSFGt66FtYN2E3uzYsd5AbVobSXEC_8Kfyp3cdJSmMQTQoqq1A---Hz2_c6-D4BnKYuNynTqCY62CU-iyBORUl7CQy38LNBJRLHD_UHUPedvL5oXa_C9ioWx-SEWB260Mor9mhY4HUjvL7OGIgIb9do9tJjpFtVD5Z1gE4WeoF4S1CxwlnmdtVFL4xs-B71Db9Trs8ivsyPW8Bvt0zp7E3rDa7DBEauQ9XY4XOSfCqqar3TPGcVBcxNel_T3d4n23oLybkV3LxAt_hIptlpLaq8srRdIaUX_bdBUfiV_zHSKU5LbWhpXgd1V7Fwov84t-FGxzfq8fGrMZ6qhv_2WUfI_8vU23CyBtXtgV8IdWDPjGmz2S9eBGtywB5SujbuqwRbBbJul-i6aLNUf7KIoDjR1Ec27nydUzmmeUekwlzIVkDPT5dSd5G55s-WSN_rsHpx3js7aXa8sLeFpSrHvxbypFTdMMBWmOmwakfupVvjr55plaDQKFqlAax7kOvQ5BSumeZaIlGpHmpjdh_XxZGwegqt0ZjKUEJNzg2jIqJypPMiFMoiEojR24EM14fKLzSAiba7oUEpidOkEgGyWFZNlICSXyF4pkbXSslYy6cv2qQzl0IHnheQsOsTRk4de3JQfB8fyfSc-Js9FmTiwvSJayy_AvVxEwoGdStQk7it0WZSOzWQ-lTHa_QgNuQMPrAT-8vGR4DH3HRgVcvTHqP46qCvHVLY8-ie97sD17ln_RJ70Bu8ew5bNpxB6oXgC67PLudlGZDlTT4vV_xO281MN |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwxV3db9MwELfGJlWTEB_lK8BYHijaHtIlsevEBSFGt24F2m0tE3uzYsd-AbXT2kqIB_4V_lXu4qSlMIknhFRVrR988fls_y6--x0hzzOaGJXrLBAMfBOWch4IrlSQsliLMI90yjF3uD_gx-fs3UXrYo18r3JhHD_E4oUbroxiv8YFfpnbvSVpKACwUa_TA4cZL1EDOLtTaMLMEziWBDYLmGTWoB04pOEXfPZ7B8Go16c8bNBD2gybnZMGfRsHwxtkg3EAIwiqhgv6qagq-YrXnDyJWjXyppS_t4OydxeSdyq5u5Fos1cgsd1eSnvtZL0ESSvH3wbO5FcMx8ymMCPWldK4DuuuQufi7OveJj8qrbmQl8_N-Uw19bffCCX_n1rvkFslrPb33Tq4S9bMuE5q_TJwoE5uuteTvsu6qpNNBNmOo_oeOCzVH-iiKA009QHL-18mWMxpnmPhMB95CjCU6WrqT6xf3mv5GIs-u0_Ou4cfO8dBWVgi0EiwHySspRUzVFAVZzpuGWHDTCv4Dq2mObiMgnIVac0iq-OQYapiZvNUZFg50iT0AVkfT8bmEfGVzk0OBmIsM4CFjLJU2cgKZQAH8SzxyFk13_LS8YdIxxQdS4mKLkMAQM2yUrKMhGQS1CslqFY61UoqQ9k5kbEceuRFYTiLDmH0GJ-XtOSnwZE87SZHGLcoU49srVjW8glgJxdceGS7sjQJuwpeFWVjM5lPZQJePwBD5pGHzgB_eXguWMJCj4wKM_pjVH8d1LVjKlse_5Net0nt9KArP_QG75-QTUemEAexeErWZ1dzswWwcqaeFWv_J0CMUbw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=Statistics+in+medicine&rft.atitle=Statistical+models+for+longitudinal+biomarkers+of+disease+onset&rft.au=SLATE%2C+E.+H&rft.au=TURNBULL%2C+B.+W&rft.date=2000-02-29&rft.pub=Wiley&rft.issn=0277-6715&rft.volume=19&rft.issue=4&rft.spage=617&rft.epage=637&rft_id=info:doi/10.1002%2F%28SICI%291097-0258%2820000229%2919%3A4%3C617%3A%3AAID-SIM360%3E3.0.CO%3B2-R&rft.externalDBID=n%2Fa&rft.externalDocID=1318969 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0277-6715&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0277-6715&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0277-6715&client=summon |