Utility of propensity score-based Bayesian borrowing of external adult data in pediatric trials: A pragmatic evaluation through a case study in acute lymphoblastic leukemia (ALL).

A fully powered randomized controlled cancer trial can be challenging to conduct in children because of difficulties in enrollment of pediatric patients due to low disease incidence. One way to improve the feasibility of trials in pediatric patients, when clinically appropriate, is through borrowing information from comparable external adult trials in the same disease. Bayesian analysis of a pediatric trial provides a way of seamlessly augmenting pediatric trial efficacy data with data from external adult trials. However, not all external adult trial subjects may be equally clinically relevant with respect to the baseline disease severity, prognostic factors, co-morbidities, and prior therapy observed in the pediatric trial of interest. The propensity score matching method provides a way of matching the external adult subjects to the pediatric trial subjects on a set of clinically determined baseline covariates, such as baseline disease severity, prognostic factors and prior therapy. The matching then allows Bayesian information borrowing from only the most clinically relevant external adult subjects. Through a case study in pediatric acute lymphoblastic leukemia (ALL), we examine the utility of propensity score matched mixture and power priors in bringing appropriate external adult efficacy information into pediatric trial efficacy assessment, and present considerations for scaling fixed borrowing from external adult data.

Exploration of baseline patient-reported side effect bother from cancer therapy.

BACKGROUND: Patient reports of expected treatment side effects are increasingly collected as part of the assessment of patient experience in clinical trials. A global side effect item that is patient-reported has the potential to inform overall tolerability. Therefore, the aim of this study was to examine the completion and distribution of such a global single-item measure of side effect burden in five cancer clinical trials. METHODS: Data from five trials from internal Food and Drug Administration databases that included the Functional Assessment of Cancer Therapy-General single-item measure of overall side effect burden (i.e. impact on degree of bother) were analyzed. Completion rates for the side effect bother item, items adjacent to this item, and two non-adjacent items on the Functional Assessment of Cancer Therapy-General that are related to health-related quality of life were calculated at the baseline assessment and at the 3-month assessment. To evaluate the distribution, the percentage of patients reporting high levels (quite a bit or very much bother) of side effect bother at baseline and 3 months was assessed. RESULTS: Completion rates for all items were at least 80% regardless of time point or trial population. However, in three of the five trials, completion rates for the side effect bother item were lower at baseline compared to adjacent and non-adjacent items. This difference was not observed at 3 months. Up to 9.4% of patients reported high levels of side effect bother at baseline. CONCLUSION: Patients may enter trials already reporting some bother from side effects. This can make interpretation of results with respect to the investigational agent under study challenging. Patients may skip an item evaluating side effect bother at baseline, suggesting some difficulty with interpretation of what is being asked. Further study of the wording and utility of a baseline side effect bother assessment is warranted.

Efficiency of Naive Estimators for Accelerated Failure Time Models under Length-Biased Sampling.

In prevalent cohort studies where subjects are recruited at a cross-section, the time to an event may be subject to length-biased sampling, with the observed data being either the forward recurrence time, or the backward recurrence time, or their sum. In the regression setting, assuming a semiparametric accelerated failure time model for the underlying event time, where the intercept parameter is absorbed into the nuisance parameter, it has been shown that the model remains invariant under these observed data set-ups and can be fitted using standard methodology for accelerated failure time model estimation, ignoring the length-bias. However, the efficiency of these estimators is unclear, owing to the fact that the observed covariate distribution, which is also length-biased, may contain information about the regression parameter in the accelerated life model. We demonstrate that if the true covariate distribution is completely unspecified, then the naive estimator based on the conditional likelihood given the covariates is fully efficient for the slope.

FDA Approval Summary: Nivolumab for the Adjuvant Treatment of Adults with Completely Resected Esophageal/Gastroesophageal Junction Cancer and Residual Pathologic Disease.

The FDA approved nivolumab on May 20, 2021, for the adjuvant treatment of completely resected (negative margins) esophageal or gastroesophageal junction cancer (EC/GEJC) in patients who had residual pathologic disease following chemoradiotherapy. The approval was based on data from the double-blind CheckMate 577 trial, which randomly allocated patients to receive nivolumab or placebo. Disease-free survival (DFS) was the primary endpoint. At the time of the final DFS analysis and the prespecified interim overall survival (OS) analysis, the estimated median DFS was 22.4 months [95% confidence interval (CI), 16.6-34.0] in the nivolumab arm versus 11.0 months (95% CI, 8.3-14.3) in the placebo arm, with an HR of 0.69 (95% CI, 0.56-0.85; two-sided P value = 0.0003). An unblinded review of OS did not indicate a detrimental effect on survival. Adverse reactions occurring in ≥20% of patients receiving nivolumab were fatigue/asthenia, diarrhea, nausea, rash, musculoskeletal pain, and cough. Approval of nivolumab is likely to change the treatment paradigm for the adjuvant treatment of patients with completely resected (negative margins) EC/GEJC who have residual pathologic disease following chemoradiotherapy based on the study results and favorable risk:benefit of nivolumab administration.

FDA Approval Summary: Capmatinib and Tepotinib for the Treatment of Metastatic NSCLC Harboring MET Exon 14 Skipping Mutations or Alterations.

The FDA approved capmatinib and tepotinib on May 6, 2020, and February 3, 2021, respectively. Capmatinib is indicated for patients with metastatic non-small cell lung cancer (mNSCLC) whose tumors have a mutation leading to mesenchymal-epithelial transition (MET) exon 14 skipping as detected by an FDA-approved test. Tepotinib is indicated for mNSCLC harboring MET exon 14 skipping alterations. The approvals were based on trials GEOMETRY mono-1 (capmatinib) and VISION (tepotinib). In GEOMETRY mono-1, overall response rate (ORR) per Blinded Independent Review Committee (BIRC) was 68% [95% confidence interval (CI), 48-84] with median duration of response (DoR) 12.6 months (95% CI, 5.5-25.3) in 28 treatment-naïve patients and 41% (95% CI: 29, 53) with median DoR 9.7 months (95% CI, 5.5-13) in 69 previously treated patients with NSCLC with mutations leading to MET exon 14 skipping. In VISION, ORR per BIRC was 43% (95% CI: 32, 56) with median DoR 10.8 months (95% CI, 6.9-not estimable) in 69 treatment-naïve patients and 43% (95% CI, 33-55) with median DoR 11.1 months (95% CI, 9.5-18.5) in 83 previously-treated patients with NSCLC harboring MET exon 14 alterations. These are the first two therapies to be FDA approved specifically for patients with metastatic NSCLC with MET exon 14 skipping.

Response of single leukemic cells to peptidase inhibitor therapy across time and dose using a microfluidic device.

Single-cell methodologies are revealing cellular heterogeneity in numerous biological processes and pathologies. For example, cancer cells are characterized by substantial heterogeneity in basal signaling and in response to perturbations, such as drug treatment. In this work, we examined the response of 678 individual U937 (human acute myeloid leukemia) cells to an aminopeptidase-inhibiting chemotherapeutic drug (Tosedostat) over the course of 95 days. Using a fluorescent reporter peptide and a microfluidic device, we quantified the rate of reporter degradation as a function of dose. While the single-cell measurements reflected ensemble results, they added a layer of detail by revealing unique degradation patterns and outliers within the larger population. Regression modeling of the data allowed us to quantitatively explore the relationships between reporter loading, incubation time, and drug dose on peptidase activity in individual cells. Incubation time was negatively correlated with the number of peptide fragment peaks observed, while peak area (which was proportional to reporter loading) was positively correlated with both the number of fragment peaks observed and the degradation rate. Notably, a statistically significant change in the number of peaks observed was identified as dose increased from 2 to 4 µM. Similarly, a significant difference in degradation rate as a function of reporter loading was observed for doses ≥2 µM compared to the 1 µM dose. These results suggest that additional enzymes may become inhibited at doses >1 µM and >2 µM, demonstrating the utility of single-cell data to yield novel biological hypotheses.