Evaluation of Technology-Enabled Monitoring of Patient-Reported Outcomes to Detect and Treat Toxic Effects Linked to Immune Checkpoint Inhibitors
Immune checkpoint inhibitors can produce distinct toxic effects that require prompt recognition and timely management. To develop a technology-enabled, dynamically adaptive protocol that can provide the accurate information needed to inform specific remedies for immune toxic effects in patients trea...
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Published in | JAMA network open Vol. 4; no. 8; p. e2122998 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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United States
American Medical Association
02.08.2021
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Abstract | Immune checkpoint inhibitors can produce distinct toxic effects that require prompt recognition and timely management.
To develop a technology-enabled, dynamically adaptive protocol that can provide the accurate information needed to inform specific remedies for immune toxic effects in patients treated with immune checkpoint inhibitors.
An open-label cohort study was conducted at a single tertiary referral center from September 6, 2019, to September 3, 2020. The median follow-up duration was 63 (interquartile range, 35.5-122) days. Fifty patients with genitourinary cancers treated with immune checkpoint inhibitors were enrolled.
A fit-for-purpose electronic platform was developed to enable active patient and care team participation. A smartphone application downloaded onto patients' personal mobile devices prompted them to report their symptoms at least 3 times per week. The set of symptoms and associated queries were paired with alert thresholds for symptoms requiring clinical action.
The primary end point of this interim analysis was feasibility, as measured by patient and care team adherence, and lack of increase in care team staffing. Operating characteristics were estimated for each symptom alert and used to dynamically adapt the alert thresholds to ensure sensitivity while reducing unnecessary alerts.
Of the 50 patients enrolled, 47 had at least 1 follow-up visit and were included in the analysis. Median age was 65 years (range, 37-86), 39 patients (83%) were men, and 39 patients (83%) had metastatic cancer, with the most common being urothelial cell carcinoma and renal cell carcinoma (22 [47%] patients each). After initial onboarding, no further care team training or additional care team staffing was required. Patients had a median study adherence rate of 74% (interquartile range, 60%-86%) and 73% of automated alerts were reviewed within 3 days by the clinic team. Symptoms with the highest positive predictive value for adverse events requiring acute intervention included dizziness (21%), nausea/vomiting (26%), and shortness of breath (14%). The symptoms most likely to result in unnecessary alerts were arthralgia and myalgia, fatigue, and cough.
The findings of this cohort study suggest an acceptable and fiscally sound method can be developed to create a dynamic learning system to detect and manage immune-related toxic effects. |
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AbstractList | This cohort study conducts an interim analysis of an electronic platform developed for patients to report symptoms possibly related to the toxic effects of immune checkpoint inhibitors. Immune checkpoint inhibitors can produce distinct toxic effects that require prompt recognition and timely management. To develop a technology-enabled, dynamically adaptive protocol that can provide the accurate information needed to inform specific remedies for immune toxic effects in patients treated with immune checkpoint inhibitors. An open-label cohort study was conducted at a single tertiary referral center from September 6, 2019, to September 3, 2020. The median follow-up duration was 63 (interquartile range, 35.5-122) days. Fifty patients with genitourinary cancers treated with immune checkpoint inhibitors were enrolled. A fit-for-purpose electronic platform was developed to enable active patient and care team participation. A smartphone application downloaded onto patients' personal mobile devices prompted them to report their symptoms at least 3 times per week. The set of symptoms and associated queries were paired with alert thresholds for symptoms requiring clinical action. The primary end point of this interim analysis was feasibility, as measured by patient and care team adherence, and lack of increase in care team staffing. Operating characteristics were estimated for each symptom alert and used to dynamically adapt the alert thresholds to ensure sensitivity while reducing unnecessary alerts. Of the 50 patients enrolled, 47 had at least 1 follow-up visit and were included in the analysis. Median age was 65 years (range, 37-86), 39 patients (83%) were men, and 39 patients (83%) had metastatic cancer, with the most common being urothelial cell carcinoma and renal cell carcinoma (22 [47%] patients each). After initial onboarding, no further care team training or additional care team staffing was required. Patients had a median study adherence rate of 74% (interquartile range, 60%-86%) and 73% of automated alerts were reviewed within 3 days by the clinic team. Symptoms with the highest positive predictive value for adverse events requiring acute intervention included dizziness (21%), nausea/vomiting (26%), and shortness of breath (14%). The symptoms most likely to result in unnecessary alerts were arthralgia and myalgia, fatigue, and cough. The findings of this cohort study suggest an acceptable and fiscally sound method can be developed to create a dynamic learning system to detect and manage immune-related toxic effects. Importance Immune checkpoint inhibitors can produce distinct toxic effects that require prompt recognition and timely management. Objective To develop a technology-enabled, dynamically adaptive protocol that can provide the accurate information needed to inform specific remedies for immune toxic effects in patients treated with immune checkpoint inhibitors. Design, Setting, and Participants An open-label cohort study was conducted at a single tertiary referral center from September 6, 2019, to September 3, 2020. The median follow-up duration was 63 (interquartile range, 35.5-122) days. Fifty patients with genitourinary cancers treated with immune checkpoint inhibitors were enrolled. Interventions A fit-for-purpose electronic platform was developed to enable active patient and care team participation. A smartphone application downloaded onto patients’ personal mobile devices prompted them to report their symptoms at least 3 times per week. The set of symptoms and associated queries were paired with alert thresholds for symptoms requiring clinical action. Main Outcomes and Measures The primary end point of this interim analysis was feasibility, as measured by patient and care team adherence, and lack of increase in care team staffing. Operating characteristics were estimated for each symptom alert and used to dynamically adapt the alert thresholds to ensure sensitivity while reducing unnecessary alerts. Results Of the 50 patients enrolled, 47 had at least 1 follow-up visit and were included in the analysis. Median age was 65 years (range, 37-86), 39 patients (83%) were men, and 39 patients (83%) had metastatic cancer, with the most common being urothelial cell carcinoma and renal cell carcinoma (22 [47%] patients each). After initial onboarding, no further care team training or additional care team staffing was required. Patients had a median study adherence rate of 74% (interquartile range, 60%-86%) and 73% of automated alerts were reviewed within 3 days by the clinic team. Symptoms with the highest positive predictive value for adverse events requiring acute intervention included dizziness (21%), nausea/vomiting (26%), and shortness of breath (14%). The symptoms most likely to result in unnecessary alerts were arthralgia and myalgia, fatigue, and cough. Conclusions and Relevance The findings of this cohort study suggest an acceptable and fiscally sound method can be developed to create a dynamic learning system to detect and manage immune-related toxic effects. |
Author | Lopez, Lidia P Van Alstine, Michael L Shaw, Leah K Elashoff, Michael Lu, Cong Oromendia, Clara Siefker-Radtke, Arlene O Shah, Amishi Y Campbell, Matthew T Msaouel, Pavlos McCord, Heather Aparicio, Ana M Subudhi, Sumit K Wang, Yinghong Siddiqui, Bilal A Zurita, Amado J Perales, Jacqueline Logothetis, Christopher Tannir, Nizar M Gao, Jianjun Chakraborty, Sandip N |
AuthorAffiliation | 4 Division of Internal Medicine, Department of Gastroenterology, Hepatology, and Nutrition, The University of Texas MD Anderson Cancer Center, Houston 3 The Ronin Project, San Mateo, California 5 Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston 1 Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston 2 Division of Pathology and Laboratory Medicine, Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston |
AuthorAffiliation_xml | – name: 4 Division of Internal Medicine, Department of Gastroenterology, Hepatology, and Nutrition, The University of Texas MD Anderson Cancer Center, Houston – name: 1 Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – name: 5 Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston – name: 2 Division of Pathology and Laboratory Medicine, Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston – name: 3 The Ronin Project, San Mateo, California |
Author_xml | – sequence: 1 givenname: Pavlos surname: Msaouel fullname: Msaouel, Pavlos organization: Division of Pathology and Laboratory Medicine, Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 2 givenname: Clara surname: Oromendia fullname: Oromendia, Clara organization: The Ronin Project, San Mateo, California – sequence: 3 givenname: Arlene O surname: Siefker-Radtke fullname: Siefker-Radtke, Arlene O organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 4 givenname: Nizar M surname: Tannir fullname: Tannir, Nizar M organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 5 givenname: Sumit K surname: Subudhi fullname: Subudhi, Sumit K organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 6 givenname: Jianjun surname: Gao fullname: Gao, Jianjun organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 7 givenname: Yinghong surname: Wang fullname: Wang, Yinghong organization: Division of Internal Medicine, Department of Gastroenterology, Hepatology, and Nutrition, The University of Texas MD Anderson Cancer Center, Houston – sequence: 8 givenname: Bilal A surname: Siddiqui fullname: Siddiqui, Bilal A organization: Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston – sequence: 9 givenname: Amishi Y surname: Shah fullname: Shah, Amishi Y organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 10 givenname: Ana M surname: Aparicio fullname: Aparicio, Ana M organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 11 givenname: Matthew T surname: Campbell fullname: Campbell, Matthew T organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 12 givenname: Amado J surname: Zurita fullname: Zurita, Amado J organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 13 givenname: Leah K surname: Shaw fullname: Shaw, Leah K organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 14 givenname: Lidia P surname: Lopez fullname: Lopez, Lidia P organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 15 givenname: Heather surname: McCord fullname: McCord, Heather organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 16 givenname: Sandip N surname: Chakraborty fullname: Chakraborty, Sandip N organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 17 givenname: Jacqueline surname: Perales fullname: Perales, Jacqueline organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston – sequence: 18 givenname: Cong surname: Lu fullname: Lu, Cong organization: The Ronin Project, San Mateo, California – sequence: 19 givenname: Michael L surname: Van Alstine fullname: Van Alstine, Michael L organization: The Ronin Project, San Mateo, California – sequence: 20 givenname: Michael surname: Elashoff fullname: Elashoff, Michael organization: The Ronin Project, San Mateo, California – sequence: 21 givenname: Christopher surname: Logothetis fullname: Logothetis, Christopher organization: Division of Cancer Medicine, Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston |
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Snippet | Immune checkpoint inhibitors can produce distinct toxic effects that require prompt recognition and timely management.
To develop a technology-enabled,... Importance Immune checkpoint inhibitors can produce distinct toxic effects that require prompt recognition and timely management. Objective To develop a... This cohort study conducts an interim analysis of an electronic platform developed for patients to report symptoms possibly related to the toxic effects of... |
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SubjectTerms | Adult Aged Aged, 80 and over Biological Monitoring - instrumentation Biological Monitoring - methods Bladder cancer Cohort Studies Female Humans Immune Checkpoint Inhibitors - therapeutic use Immune Checkpoint Inhibitors - toxicity Kidney cancer Male Middle Aged Mobile Applications Oncology Online Only Original Investigation Patient Reported Outcome Measures Patients Self report Texas Toxicity Tests - instrumentation Toxicity Tests - methods Urogenital Neoplasms - drug therapy Workforce planning |
Title | Evaluation of Technology-Enabled Monitoring of Patient-Reported Outcomes to Detect and Treat Toxic Effects Linked to Immune Checkpoint Inhibitors |
URI | https://www.ncbi.nlm.nih.gov/pubmed/34459906 https://www.proquest.com/docview/2667804315 https://pubmed.ncbi.nlm.nih.gov/PMC8406081 |
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