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  string(2556) "Background:
Two factors urgently requiring investigation are potential differences in therapeutic and adverse effects of contemporary anticancer medicines according to race and sex.
Objectives:
This study aims to summarise the key adverse effects and therapeutic outcomes of anticancer medicines registered by the FDA in the past decade according to race and sex.
Study Design and Participants:
Our research team has systematically collated information on anticancer medicines registered by the United States, Food and Drug Administration (FDA) in the past decade for the treatment of solid tumours. The key clinical trials which backbone the registration of these medicines was then collated from the product information sheets prepared by the sponsoring pharmaceutical company. The eligibility for individual participant data sharing of these clinical trials was then established with the sponsoring pharmaceutical company via email.
This study will pool available individual participant data from eligible for sharing phase 2 and 3 clinical trials to characterize the adverse event and therapeutic response profiles of contemporary treatment options for solid tumours according to race and sex. Analyses will utilise per-protocol populations and all study arms transparently shared. Summaries of trial sponsors not willing to participate individual participant data to this study will be published.
Main Outcome Measure:
Individual participant data are required for adverse event and therapeutic outcomes including clinician/patient reported adverse effects, and response, progression-free survival/ disease-free survival, and where available overall survival. The coprimary predictors of adverse event and therapeutic outcomes to be evaluated in this study will be race and sex.
Statistical Analysis:
Crude associations for adverse event will be reported based cohort frequencies of treatment induced grade ? 1, grade ? 3, and sentinel (e.g., drug cessation, hospitalisation, or death) adverse events according to race and sex. Crude associations for therapeutic outcomes will be reported based upon Kaplan Meier estimates of median time to events (e.g., median time to progression-free survival, disease-free survival, and overall survival) according to race and sex. Cox proportional hazard analysis will be used to assess the association between race/sex and the time to adverse events/ survival time. Associations will be reported as hazard ratios with 95% confidence intervals." ["project_brief_bg"]=> string(2923) "Over the last decade there has been substantial advancement in the treatment of solid tumours, including the introduction of immune checkpoint inhibitors, targeted therapies, and novel chemotherapies. However, response and toxicity to many of these medicines remains highly unpredictable. Two factors urgently requiring investigation are potential differences in therapeutic and adverse effects of contemporary anticancer medicines according to race and sex [1, 2].
Race differences are associated with a significant health disparity gap. For many common malignancies there are substantial differences in incidences according to race, while race is a phenotype for differences in genetic and tumour biology factors. Further there are inequities in drug development processes (e.g., in reporting and representation) and it is unclear if this is resulting in systematic disparities in anticancer treatment therapeutic and adverse effects [1, 3-10]. Science is also becoming increasingly aware that sex is an important modifier of health, disease and medicine efficacy [11]; however, the availability of quality information to inform sex (or gender) differences in outcomes from anticancer medicines are currently limited [2, 12]. This project will bring together individual participant data from key clinical trials to summarise the therapeutic and adverse effects of contemporary anticancer medicines according to race and sex. Being able to appraise the expected response and adverse effect profile of anticancer treatments according to racial and sex differences will enable patients and clinicians to make better patient-centred decisions.
Specifically, this project will utilise data available via Janssen?s data sharing policy and the data sharing policy of other pharmaceutical companies to summarise the therapeutic and adverse effects of contemporary anticancer medicines according to race and sex. Our research team has systematically collated information on anticancer medicines registered by the United States, Food and Drug Administration (FDA) in the past decade for the treatment of solid tumours. The key clinical trials which backbone the registration of these medicines was then collated from the product information sheets prepared by the sponsoring pharmaceutical company. The eligibility for individual participant data sharing of these clinical trials was then established with the sponsoring pharmaceutical company via email. This study will pool individual participant data from eligible for sharing phase 2 and 3 clinical trials to characterize the adverse event and therapeutic response profiles of contemporary treatment options for solid tumours according to race and sex. Summaries of trial sponsors not willing to participate individual participant data to this study will be published (noting all data requested in the study has previously been indicated as eligible for sharing)." ["project_specific_aims"]=> string(604) "The hypothesis of this research is that if the pharmaceutical industry has functioning and timely data transparency policy, then it will be leverageable to provide information summarising the therapeutic and adverse effects of contemporary anticancer medicines according to race and sex.
Specifically, this study aims to:
1. Summarise the key adverse effects of anticancer medicines registered by the FDA in the past decade according to race and sex.
2. Summarise the key therapeutic outcomes of anticancer medicine registered by the FDA in the past decade according to race and sex." ["project_study_design"]=> string(0) "" ["project_study_design_exp"]=> string(0) "" ["project_purposes"]=> array(0) { } ["project_purposes_exp"]=> string(0) "" ["project_software_used"]=> string(0) "" ["project_software_used_exp"]=> string(0) "" ["project_research_methods"]=> string(1020) "The research team has systematically collated information on anticancer medicines registered by the FDA in the past decade for the treatment of solid tumours. The key clinical trials which backbone the registration of these medicines was then collated from the product information sheets prepared by the sponsoring pharmaceutical company. The eligibility for individual participant data sharing of these clinical trials was then established with the sponsoring pharmaceutical company via email. This study will pool individual participant data from eligible for sharing phase 2 and 3 clinical trials to characterize the adverse event and therapeutic response profiles of contemporary treatment options for solid tumours according to race and sex. Analyses will utilise per-protocol populations and all study arms transparently shared. Information on clinical trials which are not transparently shared by the industry sponsor will be highlighted prior to analysis.
Please see supplementary file 1 for more details." ["project_main_outcome_measure"]=> string(379) "Individual participant data are required for adverse event and therapeutic outcomes including clinician/patient reported adverse effects according to grade or sentinel events, and response, progression-free survival/ disease-free survival, and where available overall survival. Event flag, censoring and time after treatment initiation data will be calculated for these outcomes." ["project_main_predictor_indep"]=> string(462) "The coprimary predictors of adverse event and therapeutic outcomes to be evaluated in this study will be race and sex. Race is commonly collected within clinical oncology trials, often categorised within individual participant data as white, Asian, black, and other. Sex data is most commonly within clinical oncology trials as male versus female. This study will provide summarisation of race, sex and gender data which has been recorded during trial execution." ["project_other_variables_interest"]=> string(509) "Where available summaries of available ethnicity, socioeconomic, geographical region, patient reported financial statuses, patient-reported outcomes, concomitant medicine, and medical history data according to race and sex will be reported. Exploratory analyses adjusted for age, weight, performance status, cancer type, stage of disease, and line of therapy will be conducted ? missing data will be summarised. Individual participant data on the above outcome, covariate and adjustment data will be required." ["project_stat_analysis_plan"]=> string(2533) "Primary and Secondary Endpoints:
1. Summarise the key adverse effects of anticancer medicine registered by the FDA in the past decade according to race and sex. Data are required on clinician/patient reported adverse effects according to grade or sentinel events.
2. Summarise the key therapeutic outcomes of anticancer medicine registered by the FDA in the past decade according to race and sex. Data are required for progression-free survival/ disease-free survival, and where available overall survival.
Primary predictor and sensitivity analyses:
The coprimary predictors of adverse event and therapeutic outcomes to be evaluated in this study will be race and sex. Race is commonly collected within clinical oncology trials, often categorised within individual participant data as white, Asian, black, and other. Sex data is most commonly within clinical oncology trials as male versus female. This study will provide summarisation of race, sex and gender data which has been recorded during trial execution. Where available summaries of available ethnicity, socioeconomic, geographical region, patient reported financial statuses, patient-reported outcomes, concomitant medicine, and medical history data according to race and sex will be reported. Exploratory analyses adjusted for age, weight, performance status, cancer type, stage of disease, and line of therapy will be conducted ? missing data will be summarised.
Statistical analysis:
Crude associations for adverse event will be reported based cohort frequencies of treatment induced grade ? 1, grade ? 3, and sentinel (e.g., drug cessation, hospitalisation, or death) adverse events according to race and sex. Crude associations for therapeutic outcomes will be reported based upon Kaplan Meier estimates of median time to events (e.g., median time to progression-free survival, disease-free survival, and overall survival) according to race and sex.
Cox proportional hazard analysis will be used to assess the association between race/sex and the time to adverse events/ survival time. Associations will be reported as hazard ratios with 95% confidence intervals (CI). Adjusting for between treatment and trial differences, this study will utilise a 2-stage individual-participant data meta-analysis approach. Whereby HRs and 95% CIs will initially be estimated individually for each trial arm. HRs and 95%CI will then be pooled and presented in forest plot according to conventional meta-analysis techniques. P values" ["project_timeline"]=> string(158) "Target Analysis Start Date: 7/1/22
Estimated Analysis Completion Date: 7/1/23
Manuscript Submission: 9/1/23
Reported back to YODA: 1/1/24" ["project_dissemination_plan"]=> string(1135) "A summary of the proposed research plan will be posted publicly immediately following acceptance of the research proposal. Results of all completed analyses will be published in peer-reviewed international publications and where possible presented at scientific meetings. Manuscript(s) will be targeted primarily to international oncology journals (e.g., British Journal of Cancer, International Journal of Cancer) and will be submitted as soon as possible following completion of the requisite analyses. As a related perspective piece to the scientific community (independent on the planned meta-analyses): At 9-months from initial proposal submission, summaries of trial sponsors not willing (or unable) to participate individual participant data to this study will collated with the aim to publish at 12-months (noting all data requested in the study has previously been indicated as within scope for sharing and would be considered for sharing upon receipt of a full proposal). The time from proposal submission to data access will be included in the publication, as well as a summary of the scope of data provided by each sponsor." ["project_bibliography"]=> string(2314) "

1. Stein, J.N., M. Charlot, and S. Cykert, Building Toward Antiracist Cancer Research and Practice: The Case of Precision Medicine. JCO Oncol Pract, 2021. 17(5): p. 273-277.
2. Oncology, u.S.f.M. ESMO GENDER MEDICINE TASK FORCE. 2021; Available from: https://www.esmo.org/about-esmo/organisational-structure/esmo-task-force….
3. Loree, J.M., et al., Disparity of Race Reporting and Representation in Clinical Trials Leading to Cancer Drug Approvals From 2008 to 2018. JAMA Oncology, 2019. 5(10): p. e191870-e191870.
4. Ajewole, V.B., et al., Cancer Disparities and Black American Representation in Clinical Trials Leading to the Approval of Oral Chemotherapy Drugs in the United States Between 2009 and 2019. JCO Oncol Pract, 2021. 17(5): p. e623-e628.
5. Varma, T., et al., Reporting of Study Participant Demographic Characteristics and Demographic Representation in Premarketing and Postmarketing Studies of Novel Cancer Therapeutics. JAMA Netw Open, 2021. 4(4): p. e217063.
6. Grant, S.R., et al., Racial and Ethnic Disparities Among Participants in US-Based Phase 3 Randomized Cancer Clinical Trials. JNCI Cancer Spectr, 2020. 4(5): p. pkaa060.
7. Hodges, T.R., et al., Impact of race on care, readmissions, and survival for patients with glioblastoma: an analysis of the National Cancer Database. Neurooncol Adv, 2021. 3(1): p. vdab040.
8. Yekedz, E., et al., Assessing population diversity in phase III trials of cancer drugs supporting Food and Drug Administration approval in solid tumors. Int J Cancer, 2021. 149(7): p. 1455-1462.
9. Phan, V.H., et al., Ethnic differences in drug metabolism and toxicity from chemotherapy. Expert Opin Drug Metab Toxicol, 2009. 5(3): p. 243-57.
10. Labriola, M. and D.J. George, Differences in Toxicity and Outcomes in Clinical Trial Participants From Minority Populations. American Society of Clinical Oncology Educational Book, 2021(41): p. e128-e132.
11. Mauvais-Jarvis, F., et al., Sex and gender: modifiers of health, disease, and medicine. The Lancet, 2020. 396(10250): p. 565-582.
12. zdemir, B.C., et al., Sex Differences in Efficacy and Toxicity of Systemic Treatments: An Undervalued Issue in the Era of Precision Oncology. Journal of Clinical Oncology, 2018. 36(26): p. 2680-2683.

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2022-4889

Research Proposal

Project Title: Summarising the therapeutic and adverse effects of anticancer medicines according to race and sex: pooled analysis of clinical trials

Scientific Abstract: Background:
Two factors urgently requiring investigation are potential differences in therapeutic and adverse effects of contemporary anticancer medicines according to race and sex.
Objectives:
This study aims to summarise the key adverse effects and therapeutic outcomes of anticancer medicines registered by the FDA in the past decade according to race and sex.
Study Design and Participants:
Our research team has systematically collated information on anticancer medicines registered by the United States, Food and Drug Administration (FDA) in the past decade for the treatment of solid tumours. The key clinical trials which backbone the registration of these medicines was then collated from the product information sheets prepared by the sponsoring pharmaceutical company. The eligibility for individual participant data sharing of these clinical trials was then established with the sponsoring pharmaceutical company via email.
This study will pool available individual participant data from eligible for sharing phase 2 and 3 clinical trials to characterize the adverse event and therapeutic response profiles of contemporary treatment options for solid tumours according to race and sex. Analyses will utilise per-protocol populations and all study arms transparently shared. Summaries of trial sponsors not willing to participate individual participant data to this study will be published.
Main Outcome Measure:
Individual participant data are required for adverse event and therapeutic outcomes including clinician/patient reported adverse effects, and response, progression-free survival/ disease-free survival, and where available overall survival. The coprimary predictors of adverse event and therapeutic outcomes to be evaluated in this study will be race and sex.
Statistical Analysis:
Crude associations for adverse event will be reported based cohort frequencies of treatment induced grade ? 1, grade ? 3, and sentinel (e.g., drug cessation, hospitalisation, or death) adverse events according to race and sex. Crude associations for therapeutic outcomes will be reported based upon Kaplan Meier estimates of median time to events (e.g., median time to progression-free survival, disease-free survival, and overall survival) according to race and sex. Cox proportional hazard analysis will be used to assess the association between race/sex and the time to adverse events/ survival time. Associations will be reported as hazard ratios with 95% confidence intervals.

Brief Project Background and Statement of Project Significance: Over the last decade there has been substantial advancement in the treatment of solid tumours, including the introduction of immune checkpoint inhibitors, targeted therapies, and novel chemotherapies. However, response and toxicity to many of these medicines remains highly unpredictable. Two factors urgently requiring investigation are potential differences in therapeutic and adverse effects of contemporary anticancer medicines according to race and sex [1, 2].
Race differences are associated with a significant health disparity gap. For many common malignancies there are substantial differences in incidences according to race, while race is a phenotype for differences in genetic and tumour biology factors. Further there are inequities in drug development processes (e.g., in reporting and representation) and it is unclear if this is resulting in systematic disparities in anticancer treatment therapeutic and adverse effects [1, 3-10]. Science is also becoming increasingly aware that sex is an important modifier of health, disease and medicine efficacy [11]; however, the availability of quality information to inform sex (or gender) differences in outcomes from anticancer medicines are currently limited [2, 12]. This project will bring together individual participant data from key clinical trials to summarise the therapeutic and adverse effects of contemporary anticancer medicines according to race and sex. Being able to appraise the expected response and adverse effect profile of anticancer treatments according to racial and sex differences will enable patients and clinicians to make better patient-centred decisions.
Specifically, this project will utilise data available via Janssen?s data sharing policy and the data sharing policy of other pharmaceutical companies to summarise the therapeutic and adverse effects of contemporary anticancer medicines according to race and sex. Our research team has systematically collated information on anticancer medicines registered by the United States, Food and Drug Administration (FDA) in the past decade for the treatment of solid tumours. The key clinical trials which backbone the registration of these medicines was then collated from the product information sheets prepared by the sponsoring pharmaceutical company. The eligibility for individual participant data sharing of these clinical trials was then established with the sponsoring pharmaceutical company via email. This study will pool individual participant data from eligible for sharing phase 2 and 3 clinical trials to characterize the adverse event and therapeutic response profiles of contemporary treatment options for solid tumours according to race and sex. Summaries of trial sponsors not willing to participate individual participant data to this study will be published (noting all data requested in the study has previously been indicated as eligible for sharing).

Specific Aims of the Project: The hypothesis of this research is that if the pharmaceutical industry has functioning and timely data transparency policy, then it will be leverageable to provide information summarising the therapeutic and adverse effects of contemporary anticancer medicines according to race and sex.
Specifically, this study aims to:
1. Summarise the key adverse effects of anticancer medicines registered by the FDA in the past decade according to race and sex.
2. Summarise the key therapeutic outcomes of anticancer medicine registered by the FDA in the past decade according to race and sex.

Study Design:

What is the purpose of the analysis being proposed? Please select all that apply.:

Software Used:

Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study: The research team has systematically collated information on anticancer medicines registered by the FDA in the past decade for the treatment of solid tumours. The key clinical trials which backbone the registration of these medicines was then collated from the product information sheets prepared by the sponsoring pharmaceutical company. The eligibility for individual participant data sharing of these clinical trials was then established with the sponsoring pharmaceutical company via email. This study will pool individual participant data from eligible for sharing phase 2 and 3 clinical trials to characterize the adverse event and therapeutic response profiles of contemporary treatment options for solid tumours according to race and sex. Analyses will utilise per-protocol populations and all study arms transparently shared. Information on clinical trials which are not transparently shared by the industry sponsor will be highlighted prior to analysis.
Please see supplementary file 1 for more details.

Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study: Individual participant data are required for adverse event and therapeutic outcomes including clinician/patient reported adverse effects according to grade or sentinel events, and response, progression-free survival/ disease-free survival, and where available overall survival. Event flag, censoring and time after treatment initiation data will be calculated for these outcomes.

Main Predictor/Independent Variable and how it will be categorized/defined for your study: The coprimary predictors of adverse event and therapeutic outcomes to be evaluated in this study will be race and sex. Race is commonly collected within clinical oncology trials, often categorised within individual participant data as white, Asian, black, and other. Sex data is most commonly within clinical oncology trials as male versus female. This study will provide summarisation of race, sex and gender data which has been recorded during trial execution.

Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study: Where available summaries of available ethnicity, socioeconomic, geographical region, patient reported financial statuses, patient-reported outcomes, concomitant medicine, and medical history data according to race and sex will be reported. Exploratory analyses adjusted for age, weight, performance status, cancer type, stage of disease, and line of therapy will be conducted ? missing data will be summarised. Individual participant data on the above outcome, covariate and adjustment data will be required.

Statistical Analysis Plan: Primary and Secondary Endpoints:
1. Summarise the key adverse effects of anticancer medicine registered by the FDA in the past decade according to race and sex. Data are required on clinician/patient reported adverse effects according to grade or sentinel events.
2. Summarise the key therapeutic outcomes of anticancer medicine registered by the FDA in the past decade according to race and sex. Data are required for progression-free survival/ disease-free survival, and where available overall survival.
Primary predictor and sensitivity analyses:
The coprimary predictors of adverse event and therapeutic outcomes to be evaluated in this study will be race and sex. Race is commonly collected within clinical oncology trials, often categorised within individual participant data as white, Asian, black, and other. Sex data is most commonly within clinical oncology trials as male versus female. This study will provide summarisation of race, sex and gender data which has been recorded during trial execution. Where available summaries of available ethnicity, socioeconomic, geographical region, patient reported financial statuses, patient-reported outcomes, concomitant medicine, and medical history data according to race and sex will be reported. Exploratory analyses adjusted for age, weight, performance status, cancer type, stage of disease, and line of therapy will be conducted ? missing data will be summarised.
Statistical analysis:
Crude associations for adverse event will be reported based cohort frequencies of treatment induced grade ? 1, grade ? 3, and sentinel (e.g., drug cessation, hospitalisation, or death) adverse events according to race and sex. Crude associations for therapeutic outcomes will be reported based upon Kaplan Meier estimates of median time to events (e.g., median time to progression-free survival, disease-free survival, and overall survival) according to race and sex.
Cox proportional hazard analysis will be used to assess the association between race/sex and the time to adverse events/ survival time. Associations will be reported as hazard ratios with 95% confidence intervals (CI). Adjusting for between treatment and trial differences, this study will utilise a 2-stage individual-participant data meta-analysis approach. Whereby HRs and 95% CIs will initially be estimated individually for each trial arm. HRs and 95%CI will then be pooled and presented in forest plot according to conventional meta-analysis techniques. P values

Narrative Summary: Over the last decade there has been substantial advancement in the treatment of solid tumours, including the introduction of immune checkpoint inhibitors, targeted therapies, and novel chemotherapies. However, response and toxicity to many of these medicines remains highly unpredictable. Two factors urgently requiring investigation are potential differences in therapeutic and adverse effects of contemporary anticancer medicines according to race and sex.

Project Timeline: Target Analysis Start Date: 7/1/22
Estimated Analysis Completion Date: 7/1/23
Manuscript Submission: 9/1/23
Reported back to YODA: 1/1/24

Dissemination Plan: A summary of the proposed research plan will be posted publicly immediately following acceptance of the research proposal. Results of all completed analyses will be published in peer-reviewed international publications and where possible presented at scientific meetings. Manuscript(s) will be targeted primarily to international oncology journals (e.g., British Journal of Cancer, International Journal of Cancer) and will be submitted as soon as possible following completion of the requisite analyses. As a related perspective piece to the scientific community (independent on the planned meta-analyses): At 9-months from initial proposal submission, summaries of trial sponsors not willing (or unable) to participate individual participant data to this study will collated with the aim to publish at 12-months (noting all data requested in the study has previously been indicated as within scope for sharing and would be considered for sharing upon receipt of a full proposal). The time from proposal submission to data access will be included in the publication, as well as a summary of the scope of data provided by each sponsor.

Bibliography:

1. Stein, J.N., M. Charlot, and S. Cykert, Building Toward Antiracist Cancer Research and Practice: The Case of Precision Medicine. JCO Oncol Pract, 2021. 17(5): p. 273-277.
2. Oncology, u.S.f.M. ESMO GENDER MEDICINE TASK FORCE. 2021; Available from: https://www.esmo.org/about-esmo/organisational-structure/esmo-task-force….
3. Loree, J.M., et al., Disparity of Race Reporting and Representation in Clinical Trials Leading to Cancer Drug Approvals From 2008 to 2018. JAMA Oncology, 2019. 5(10): p. e191870-e191870.
4. Ajewole, V.B., et al., Cancer Disparities and Black American Representation in Clinical Trials Leading to the Approval of Oral Chemotherapy Drugs in the United States Between 2009 and 2019. JCO Oncol Pract, 2021. 17(5): p. e623-e628.
5. Varma, T., et al., Reporting of Study Participant Demographic Characteristics and Demographic Representation in Premarketing and Postmarketing Studies of Novel Cancer Therapeutics. JAMA Netw Open, 2021. 4(4): p. e217063.
6. Grant, S.R., et al., Racial and Ethnic Disparities Among Participants in US-Based Phase 3 Randomized Cancer Clinical Trials. JNCI Cancer Spectr, 2020. 4(5): p. pkaa060.
7. Hodges, T.R., et al., Impact of race on care, readmissions, and survival for patients with glioblastoma: an analysis of the National Cancer Database. Neurooncol Adv, 2021. 3(1): p. vdab040.
8. Yekedz, E., et al., Assessing population diversity in phase III trials of cancer drugs supporting Food and Drug Administration approval in solid tumors. Int J Cancer, 2021. 149(7): p. 1455-1462.
9. Phan, V.H., et al., Ethnic differences in drug metabolism and toxicity from chemotherapy. Expert Opin Drug Metab Toxicol, 2009. 5(3): p. 243-57.
10. Labriola, M. and D.J. George, Differences in Toxicity and Outcomes in Clinical Trial Participants From Minority Populations. American Society of Clinical Oncology Educational Book, 2021(41): p. e128-e132.
11. Mauvais-Jarvis, F., et al., Sex and gender: modifiers of health, disease, and medicine. The Lancet, 2020. 396(10250): p. 565-582.
12. zdemir, B.C., et al., Sex Differences in Efficacy and Toxicity of Systemic Treatments: An Undervalued Issue in the Era of Precision Oncology. Journal of Clinical Oncology, 2018. 36(26): p. 2680-2683.