Lampson B, Zakharyan A, Shimony SO, Shi H, Deangelo D. Analysis of avapritinib clinical trial data generates a highly accurate predictive model for advanced systemic mastocytosis versus indolent systemic mastocytosis based on peripheral blood testing. Blood. 2024;144(suppl 1):107.

Analysis of Avapritinib Clinical Trial Data Generates a Highly Accurate Predictive Model for Advanced Systemic Mastocytosis Versus Indolent Systemic Mastocytosis Based on Peripheral Blood Testing

Background: Treatment with PD-(L)1 blocking antibodies has dramatically improved outcomes across multiple cancer types. Such benefits must be carefully weighed against the risks of serious immune-related adverse events (irAEs) involving various organs, the occurrence patterns of which have not yet been well characterized. This large novel analysis of pooled clinical trial data submitted to FDA aims at uncovering and gaining deeper insights into the multiorgan patterns of irAEs associated with these agents. Methods: This retrospective pooled analysis is based on patient-level, monotherapy, PD-(L)1 blocking antibody data from 18 clinical trials completed between 2019 and 2023, supporting FDA approvals across 7 cancer types. Only FDA authors had access to and analyzed patient level data. Patients with irAEs were identified using each PD-(L)1 development program’s pre-defined definitions based on MedDRA preferred terms. Preferred terms were grouped into 30 irAEs based on the involved organs. IrAEs starting before or within 7 days of the end date of the preceding irAE, were considered co-occurring. Results: Among the 5863 patients, 64% (n=3771) had at least one irAE; the most common irAEs (>10%) were skin reaction (53.5%), colitis/diarrhea (33.2%), hepatitis (23%), hypothyroidism (19.3%), and nephritis/renal dysfunction (11.7%). 50% (n= 1890) had more than one irAE type, with 59.7% experiencing 2, 24.8% experiencing 3, 9.7% experiencing 4, and 5.8% experiencing 5 to a maximum of 8 distinct irAE types, regardless of timing during their treatment course. Median time-to-onset of irAE in patients with a single type of irAE was 45 days while median time-to-onset of first irAE in subjects with more than one type of irAE was 30.5 days. Among the 1743 patients evaluable for co-occurrence analysis, 1285 (73.7%) experienced co-occurring irAEs. The 5 most frequently co-occurring irAEs were: skin reaction and colitis/diarrhea (15.8%); skin reaction and hepatitis (8.2%); skin reaction and hypothyroidism (7.5%); skin reaction and nephritis/renal dysfunction (4.8%); and colitis/diarrhea and hepatitis (4.2%). Conclusions: This is the largest study of patient level clinical trial data evaluating the incidence and occurrence patterns of multi-system irAEs. The study demonstrated that the median time-to-onset of the first irAE was shorter for patients who experienced multi-organ irAEs than in those with single organ irAEs. Notably, half of the patients with an irAE experienced more than one distinct irAE during treatment, the majority of whom demonstrated co-occurrence of irAEs. These findings underscore the importance of vigilant monitoring and comprehensive management strategies to address the interconnected nature of irAEs, aiding providers in understanding, predicting, and managing patients experiencing irAEs. Citation Format: Abhilasha Nair, Matthew J. Hadfield, Yue Huang, Flora Mulkey, Ilynn Bulatao, Marc R. Theoret, Kerry L. Reynolds. Characterization of multi-organ system involvement of immune-related adverse events after anti-PD-(L)1 monotherapies: A pooled analysis of clinical trial data submitted to FDA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3228.

ObjectivesTo examine the validity and statistical limitations of exploratory analyses of clinical trial data commonly requested by agencies responsible for determining which medical products may be financed or reimbursed by a healthcare system.DesignThis was a retrospective review of efficacy and safety analyses conducted for German Health Technology Assessment (HTA) evaluations with a decision date between 2015 and 2020, and an illustrative safety-related exploratory analysis of data from two phase III clinical trials of verubecestat (an anti-amyloid drug whose development was stopped for lack of efficacy) as would be mandated by the German HTA agency.ResultsWe identified 422 HTA evaluations of 404 randomised controlled clinical trials. For 140 trials (34.7%), the evaluation was based on subpopulations of participants in the originating confirmatory trial (175 subpopulations were assessed). In 57% (100 of 175), the subpopulation sample size was 50% or less of the original study population. Detailed analysis of five evaluations based on subpopulations of the original trial is presented. The safety-related exploratory analysis of verubecestat led to 206 statistical analyses for treatments and 812 treatment-by-subgroup interaction tests. Of 31 safety endpoints with an elevated HR (suggesting association with drug treatment), the HR for 81% of these (25 of 31) was not elevated in both trials. Of the 812 treatment-by-subgroup interactions evaluated, 26 had an elevated HR for a subgroup in one trial, but only 1 was elevated in both trials.ConclusionsMany HTA evaluations rely on subpopulation analyses and numerous post hoc statistical hypothesis tests. Subpopulation analysis may lead to loss of statistical power and uncontrolled influences of random imbalances. Multiple testing may introduce spurious findings. Decisions about benefits of medical products should therefore not rely on exploratory analyses of clinical trial data but rather on prospective clinical studies and careful synthesis of all available evidence based on prespecified criteria.

<div>Abstract<p>The FDA Oncology Center of Excellence recently launched a crowdsourcing pilot to request ideas from the scientific community for research questions that FDA could address with pooled analyses of clinical trial data submitted to the agency for regulatory purposes. This effort builds on FDA's track record of publishing pooled analyses to explore scientific questions that cannot be addressed in a single trial due to limited sample size. The research crowdsourcing pilot tested a new approach for obtaining external input on regulatory science activities, because FDA is generally unable to share patient-level data outside of the agency due to federal disclosure laws and regulations protecting different types of data submitted in regulatory applications. We received 29 submissions over the 28-day crowdsourcing campaign, including one research idea that we are exploring for possible follow-up. Based on our experience with this pilot, we learned that crowdsourcing is a promising new approach to gather external input and feedback. We identified opportunities to build understanding in the external oncology community about the types of data typically included in regulatory applications and expand the dissemination of published FDA pooled analyses to help inform future drug development and clinical practice.</p></div>

<div>Abstract<p>The FDA Oncology Center of Excellence recently launched a crowdsourcing pilot to request ideas from the scientific community for research questions that FDA could address with pooled analyses of clinical trial data submitted to the agency for regulatory purposes. This effort builds on FDA's track record of publishing pooled analyses to explore scientific questions that cannot be addressed in a single trial due to limited sample size. The research crowdsourcing pilot tested a new approach for obtaining external input on regulatory science activities, because FDA is generally unable to share patient-level data outside of the agency due to federal disclosure laws and regulations protecting different types of data submitted in regulatory applications. We received 29 submissions over the 28-day crowdsourcing campaign, including one research idea that we are exploring for possible follow-up. Based on our experience with this pilot, we learned that crowdsourcing is a promising new approach to gather external input and feedback. We identified opportunities to build understanding in the external oncology community about the types of data typically included in regulatory applications and expand the dissemination of published FDA pooled analyses to help inform future drug development and clinical practice.</p></div>

The FDA Oncology Center of Excellence recently launched a crowdsourcing pilot to request ideas from the scientific community for research questions that FDA could address with pooled analyses of clinical trial data submitted to the agency for regulatory purposes. This effort builds on FDA's track record of publishing pooled analyses to explore scientific questions that cannot be addressed in a single trial due to limited sample size. The research crowdsourcing pilot tested a new approach for obtaining external input on regulatory science activities, because FDA is generally unable to share patient-level data outside of the agency due to federal disclosure laws and regulations protecting different types of data submitted in regulatory applications. We received 29 submissions over the 28-day crowdsourcing campaign, including one research idea that we are exploring for possible follow-up. Based on our experience with this pilot, we learned that crowdsourcing is a promising new approach to gather external input and feedback. We identified opportunities to build understanding in the external oncology community about the types of data typically included in regulatory applications and expand the dissemination of published FDA pooled analyses to help inform future drug development and clinical practice.

<div>Abstract<p>The FDA Oncology Center of Excellence recently launched a crowdsourcing pilot to request ideas from the scientific community for research questions that FDA could address with pooled analyses of clinical trial data submitted to the agency for regulatory purposes. This effort builds on FDA’s track record of publishing pooled analyses to explore scientific questions that cannot be addressed in a single trial due to limited sample size. The research crowdsourcing pilot tested a new approach for obtaining external input on regulatory science activities, because FDA is generally unable to share patient-level data outside of the agency due to federal disclosure laws and regulations protecting different types of data submitted in regulatory applications. We received 29 submissions over the 28-day crowdsourcing campaign, including one research idea that we are exploring for possible follow up. Based on our experience with this pilot, we learned that crowdsourcing is a promising new approach to gather external input and feedback. We identified opportunities to build understanding in the external oncology community about the types of data typically included in regulatory applications and expand dissemination of published FDA pooled analyses to help inform future drug development and clinical practice.</p></div>

Interim analyses of clinical trial data are frequently used to provide evidence to obtain marketing authorization for new drugs. However, results from such analyses may not reflect true estimates of relative effectiveness when trial follow-up is complete. Survival results, available at 2 time points from a breast cancer clinical trial, were compared to test the hypothesis that using immature data and a widely used right-censoring rule leads to biased survival estimates. Kaplan-Meier progression-free and overall survival data from 2 published CLEOPATRA trial reports (2012 and 2014) were digitized. Overlaying these results highlighted divergent trends. Parametric functions were fitted to both data sets but did not indicate consistent patterns that could be used as a basis for long-term extrapolation. Heavy censoring of patients in the early data cut coincides with sudden changes in hazard trends and survival patterns, supporting the hypothesis of censoring bias. This challenges the validity of estimates of clinical benefit (progression-free survival and overall survival) based on extrapolation of results from interim analyses of trial data, using a commonly employed censoring rule.

How Median Follow-up Time Informs Survival Outcomes: Lessons from a Trial of Acute Myeloid Patients Treated with Venetoclax and Azacitidine

BackgroundGreater transparency, including sharing of patient-level data for further research, is an increasingly important topic for organisations who sponsor, fund and conduct clinical trials. This is a major paradigm shift with the aim of maximising the value of patient-level data from clinical trials for the benefit of future patients and society. We consider the analysis of shared clinical trial data in three broad categories: (1) reanalysis - further investigation of the efficacy and safety of the randomized intervention, (2) meta-analysis, and (3) supplemental analysis for a research question that is not directly assessing the randomized intervention.DiscussionIn order to support appropriate interpretation and limit the risk of misleading findings, analysis of shared clinical trial data should have a pre-specified analysis plan. However, it is not generally possible to limit bias and control multiplicity to the extent that is possible in the original trial design, conduct and analysis, and this should be acknowledged and taken into account when interpreting results. We highlight a number of areas where specific considerations arise in planning, conducting, interpreting and reporting analyses of shared clinical trial data. A key issue is that that these analyses essentially share many of the limitations of any post hoc analyses beyond the original specified analyses. The use of individual patient data in meta-analysis can provide increased precision and reduce bias. Supplemental analyses are subject to many of the same issues that arise in broader epidemiological analyses. Specific discussion topics are addressed within each of these areas.SummaryIncreased provision of patient-level data from industry and academic-led clinical trials for secondary research can benefit future patients and society. Responsible data sharing, including transparency of the research objectives, analysis plans and of the results will support appropriate interpretation and help to address the risk of misleading results and avoid unfounded health scares.

Positioning Infliximab and Vedolizumab in the Treatment of Moderate-to-Severe Ulcerative Colitis

Circumstances in which both randomized controlled trial and observational study data are available provide an important opportunity to identify biases and improve study design and analysis procedures. In addition, joint analyses of data from the two sources can extend clinical trial findings. The US Women's Health Initiative includes randomized controlled trials of use of estrogen by posthysterectomy women and of estrogen plus progestin by women with a uterus, along with corresponding observational study components. In this paper, for coronary heart disease, stroke, and venous thromboembolism, results are first presented from joint analysis of estrogen clinical trial and observational study data to show that residual bias patterns are similar to those previously reported for estrogen plus progestin. These findings support certain combined analyses of the observational data on estrogen and the estrogen plus progestin clinical trial and observational study data to give adjusted observational study estimates of estrogen treatment effects. The resulting treatment effect estimates are compared with corresponding clinical trial estimates, and parallel analyses are also presented for estrogen plus progestin. An application to postmenopausal hormone treatment effects on coronary heart disease among younger women is also provided.

Tyrosine kinase inhibitors for the treatment of indolent systemic mastocytosis: Are we there yet?

Painful diabetic neuropathy is common and adversely affects patients' quality of life and function. Several treatment options exist, but their relative efficacy and value are unknown. To determine the relative efficacy, costs and cost effectiveness of the first-line treatment options for painful diabetic neuropathy. Published and unpublished clinical trial and cross-sectional data were incorporated into a decision analytic model to estimate the net health and cost consequences of treatment for painful diabetic peripheral neuropathy over 3-month (base case), 1-month and 6-month timeframes. Efficacy was measured in QALYs, and costs were measured in $US, year 2006 values, using a US third-party payer perspective. The patients included in the model were outpatients with moderate to severe pain associated with diabetic peripheral neuropathy and no contraindications to treatment with tricyclic antidepressants. Four medications were compared: desipramine 100 mg/day, gabapentin 2400 mg/day, pregabalin 300 mg/day and duloxetine 60 mg/day. Desipramine and duloxetine were both more effective and less expensive than gabapentin and pregabalin in the base-case analysis and through a wide range of sensitivity analyses. Duloxetine offered borderline value compared with desipramine in the base case ($US47,700 per QALY), but not when incorporating baseline-observation-carried-forward analyses of the clinical trial data ($US867,000 per QALY). The results were also sensitive to the probability of obtaining pain relief with duloxetine. Desipramine (100 mg/day) and duloxetine (60 mg/day) appear to be more cost effective than gabapentin or pregabalin for treating painful diabetic neuropathy. The estimated value of duloxetine relative to desipramine depends on the assumptions made in the statistical analyses of clinical trial data.

Dietary Amino Acids and Blood Pressure: A Cohort Study of Patients With Cardiovascular Disease