Uncovering nativity disparities in cancer patterns: Multiple imputation strategy to handle missing nativity data in the Surveillance, Epidemiology, and End Results data file

• Published in: Cancer Vol. 120; no. 8; pp. 1203 - 1211
• Main Authors: Montealegre, Jane R., Zhou, Renke, Amirian, E. Susan, Scheurer, Michael E.
• Format: Journal Article
• Language: English
• Published: Hoboken, NJ Wiley-Blackwell 15.04.2014
• Subjects: Adult; Aged; Biological and medical sciences; Colorectal Neoplasms - ethnology; Emigration and Immigration; Female; Health Status Disparities; Hispanic Americans; Humans; Logistic Models; Male; Medical sciences; Middle Aged; multiple imputation; Multiple tumors. Solid tumors. Tumors in childhood (general aspects); Neoplasms - ethnology; Neoplasms - mortality; Prostatic Neoplasms - ethnology; Residence Characteristics; SEER Program; Surveillance, Epidemiology, and End Results (SEER) program; Tumors; Uterine Cervical Neoplasms - ethnology; United States; North America; America; and End Results (SEER) program; Multiple; Program; Hispanic Americans; Emigration; health status disparities; multiple imputation; Malignant tumor; Latinamerican; Epidemiology; Cancerology; Health status; Surveillance; Immigration; Strategy; Disparity; emigration and immigration; File; Cancer; Surveillance, Epidemiology, and End Results (SEER) program
• ISSN: 0008-543X; 1097-0142
• DOI: 10.1002/cncr.28533

BACKGROUND Although birthplace data are routinely collected in the participating Surveillance, Epidemiology, and End Results (SEER) registries, such data are missing in a nonrandom manner for a large percentage of cases. This hinders analysis of nativity‐related cancer disparities. In the current study, the authors evaluated multiple imputation of nativity status among Hispanic patients diagnosed with cervical, prostate, and colorectal cancer and demonstrated the effect of multiple imputation on apparent nativity disparities in survival. METHODS Multiple imputation by logistic regression was used to generate nativity values (US‐born vs foreign‐born) using a priori‐defined variables. The accuracy of the method was evaluated among a subset of cases. Kaplan‐Meier curves were used to illustrate the effect of imputation by comparing survival among US‐born and foreign‐born Hispanics, with and without imputation of nativity. RESULTS Birthplace was missing for 31%, 49%, and 39%, respectively, of cases of cervical, prostate, and colorectal cancer. The sensitivity of the imputation strategy for detecting foreign‐born status was ≥ 90% and the specificity was ≥ 86%. The agreement between the true and imputed values was ≥ 0.80 and the misclassification error was ≤ 10%. Kaplan‐Meier survival curves indicated different associations between nativity and survival when nativity was imputed versus when cases with missing birthplace were omitted from the analysis. CONCLUSIONS Multiple imputation using variables available in the SEER data file can be used to accurately detect foreign‐born status. This simple strategy may help researchers to disaggregate analyses by nativity and uncover important nativity disparities in regard to cancer diagnosis, treatment, and survival. Cancer 2014;120:1203–1211. © 2014 American Cancer Society. Multiple imputation using variables available in the Surveillance, Epidemiology, and End Results (SEER) data file can be used to accurately detect foreign‐born status among the large percentage of SEER cases with missing birthplace information. This strategy will aid researchers in disaggregating analyses by nativity status and uncover important nativity disparities in regard to cancer diagnosis, treatment, and survival.