FDA Approval Summary: Nivolumab Plus Ipilimumab for the Treatment of Patients with Hepatocellular Carcinoma Previously Treated with Sorafenib.

On March 10, 2020, the U.S. Food and Drug Administration (FDA) granted accelerated approval to nivolumab in combination with ipilimumab for the treatment of patients with hepatocellular carcinoma (HCC) previously treated with sorafenib. The recommended approved dosage was nivolumab 1 mg/kg i.v. plus ipilimumab 3 mg/kg i.v. every 3 weeks for four cycles, followed by nivolumab 240 mg i.v. every 2 weeks. The approval was based on data from cohort 4 of CheckMate 040, which randomized patients with advanced unresectable or metastatic HCC previously treated with or who were intolerant to sorafenib to receive one of three different dosing regimens of nivolumab in combination with ipilimumab. Investigator-assessed overall response rate (ORR) was the primary endpoint, and ORR assessed by blinded independent central review (BICR) was an exploratory endpoint. BICR-assessed ORR and duration of response (DoR) form the primary basis of the FDA's regulatory decision, and BICR-assessed ORR was comparable in all three arms at 31%-32% with 95% confidence interval [CI] 18%-47%. The DoR ranged from 17.5 to 22.2 months across the three arms, with overlapping 95% CIs. Adverse events (AEs) were generally consistent with the known AE profiles of nivolumab and ipilimumab, and no new safety events were identified. This article summarizes the FDA review of the data supporting the approval of nivolumab and ipilimumab for the treatment of HCC. IMPLICATIONS FOR PRACTICE: Nivolumab and ipilimumab combination therapy is another option for patients with advanced hepatocellular carcinoma who experience radiographic progression during or after sorafenib or sorafenib intolerance. No new toxicities were identified, but, as expected, increased toxicity was observed with the addition of ipilimumab to nivolumab as compared with nivolumab alone, which is also approved for the same indication. Whether to administer nivolumab as a single agent or in combination with ipilimumab is expected to be a joint decision between the oncologist and patient, taking into consideration the potential for a higher likelihood of response and the potentially higher rate of toxicity with the combination.

Simultaneous confidence interval methods for analytical similarity assessment.

In analytical similarity assessment of a biosimilar product, key quality attributes of the test and reference products need to be shown statistically similar. When there were multiple references, similarity among the reference products is also required. We proposed a simultaneous confidence approach based on the fiducial inference theory as an alternative to the pairwise comparison method. Three versions with two types of simultaneous confidence intervals for each version were proposed based on different assumptions of the population variance. We conducted extensive simulation studies to compare the performance of our proposed method and the pairwise method, and provided examples to illustrate the concern of using pairwise method.

On assessing bioequivalence and interchangeability between generics based on indirect comparisons.

As more and more generics become available in the market place, the safety/efficacy concerns may arise as the result of interchangeably use of approved generics. However, bioequivalence assessment for regulatory approval among generics of the innovative drug product is not required. In practice, approved generics are often used interchangeably without any mechanism of safety monitoring. In this article, based on indirect comparisons, we proposed several methods to assessing bioequivalence and interchangeability between generics. The applicability of the methods and the similarity assumptions were discussed, as well as the inappropriateness of directly adopting adjusted indirect comparison to the field of generics' comparison. Besides, some extensions were given to take into consideration the important topics in clinical trials for bioequivalence assessments, for example, multiple comparisons and simultaneously testing bioequivalence among three generics. Extensive simulation studies were conducted to investigate the performances of the proposed methods. The studies of malaria generics and HIV/AIDS generics prequalified by the WHO were used as real examples to demonstrate the use of the methods. Copyright © 2017 John Wiley & Sons, Ltd.

FDA Approval Summary: Durvalumab and Pembrolizumab, Immune Checkpoint Inhibitors for the Treatment of Biliary Tract Cancer.

On September 2, 2022, the Food and Drug Administration (FDA) approved durvalumab in combination with cisplatin and gemcitabine, for the treatment of patients with unresectable or metastatic biliary tract cancers (BTC). On October 31, 2023, the FDA approved pembrolizumab in combination with cisplatin and gemcitabine for the same indication. Approvals were based on two randomized, multiregional, placebo-controlled trials that randomly allocated patients to receive durvalumab (TOPAZ-1) or pembrolizumab (KEYNOTE-966) in combination with chemotherapy or placebo in combination with chemotherapy. Overall survival (OS) was the primary endpoint in both studies. In both studies, a statistically significant and clinically meaningful improvement in OS was demonstrated. In the TOPAZ-1 trial, the median OS of patients receiving durvalumab was 12.8 months [95% confidence interval (CI), 11.1-14.0] and 11.5 months (95% CI, 10.1-12.5) in patients receiving placebo [hazard ratio (HR), 0.80 (95% CI, 0.66-0.97)]. In the KEYNOTE-966 trial, the median OS of patients receiving pembrolizumab was 12.7 months (95% CI, 11.5-13.6) and 10.9 months (95% CI, 9.9-11.6) in patients receiving placebo [HR, 0.83 (95% CI, 0.72-0.95)]. The addition of checkpoint inhibitors to standard of care chemotherapy for this indication did not reveal any new adverse event signals, and the safety profile was generally consistent with the known clinical experience with durvalumab, pembrolizumab, and the backbone chemotherapy regimen. The approvals of durvalumab and pembrolizumab in combination with standard of care cisplatin and gemcitabine for the treatment of unresectable or metastatic BTC add two new therapeutic options for these patients.

Comparing the response rates for superiority, noninferiority and equivalence testing with multiple-to-one matched binary data.

Paired and multiple-to-one matched data have often been collected in clinical trials and epidemiological safety studies. When the response is binary, the sample size and power are determined by the discordant pairs or matched sets. Fixed sample size determination in assessing response rate difference of superiority, noninferiority, and equivalence tests of paired binary data has been discussed by Lu and Bean (1995)Nam (1997), and Liu et al. (2002). We extend the results of Lu and Bean (1995)Nam (1997), and Liu et al. (2002) to more general cases of multiple-to-one matched binary data. We further examine two issues regarding such tests. First, we examine the issue of simultaneous test and two-stage test for both superiority and noninferiority/equivalence hypotheses. Although, as discussed in Nam (1997) and Liu et al. (2002), the standard errors restricted to null hypothesis are different between superiority and noninferiority test, the monotonic property of the two tests makes the simultaneous testing and switching between the hypotheses valid. Second, in practice, the joint distribution of matched responses is often unknown, and thus determining the sample size using only the background information of the control group could be inefficient. Furthermore, for noninferiority or equivalence tests, the sample sizes are often determined using the unrealistic alternative hypothesis that the response rates of both treatments are identical. We propose to use a two-stage adaptive design strategy for sample size reestimation that uses the interim information to improve the efficiency.

FDA Approval Summary: Tucatinib with Trastuzumab for Advanced Unresectable or Metastatic, Chemotherapy Refractory, HER2-Positive RAS Wild-Type Colorectal Cancer.

On January 19, 2023, the FDA granted accelerated approval to tucatinib in combination with trastuzumab for the treatment of patients with unresectable or metastatic RAS wild-type, HER2-positive colorectal cancer who have received prior treatment with fluoropyrimidine, oxaliplatin, and irinotecan. Approval was based on the pooled analysis of patients receiving tucatinib in combination with trastuzumab in MOUNTAINEER (NCT03043313), an open-label, multicenter trial. The primary endpoint was overall response rate (ORR) by RECIST 1.1 as per blinded central review committee (BIRC) assessment. The main secondary endpoint was duration of response (DOR) per BIRC assessment. Eighty-four eligible patients received the combination tucatinib and trastuzumab. With a median follow-up of 16 months, the ORR was 38% [95% confidence interval (CI): 28-49] and median DOR was 12.4 months (95% CI: 8.5-20.5); 81% of responders had a response lasting more than 6 months. The most common adverse reactions observed in at least 20% of patients receiving tucatinib in combination with trastuzumab were diarrhea, fatigue, rash, nausea, abdominal pain, infusion-related reactions, and fever. FDA concluded that the magnitude of ORR and durable responses observed in patients treated with tucatinib in combination with trastuzumab in the MOUNTAINEER trial are clinically meaningful, particularly in the context of a disease with estimated survival of 6-7 months with available therapy. This is the first approval for the subset of patients with HER2-positive colorectal cancer. This article summarizes the FDA's thought process and review of the data supporting this accelerated approval.

FDA Approval Summary: Pembrolizumab for the Treatment of Tumor Mutational Burden-High Solid Tumors.

The FDA approved pembrolizumab on June 16, 2020, for the treatment of adult and pediatric patients with unresectable or metastatic tumor mutational burden-high [TMB-H; ≥10 mutations/megabase (mut/Mb)] solid tumors, as determined by an FDA-approved test, that have progressed following prior treatment and who have no satisfactory alternative treatment options. FDA granted the approval based on a clinically important overall response rate (29%; 95% confidence interval, 21-39) and duration of response (57% of responses lasting ≥ 12 months) in the subset of patients with TMB-H solid tumors (n = 102) spanning nine different tumor types enrolled in a multicenter single-arm trial (KEYNOTE-158). The efficacy of pembrolizumab was supported by the results of whole-exome sequencing (WES) analyses of TMB in additional patients enrolled across multiple pembrolizumab clinical trials, and a scientific understanding of the effects of PD-1 inhibition. Overall, the adverse event profile of pembrolizumab was similar to the adverse event profile observed in prior trials that supported the approval of pembrolizumab in other indications. This approval of pembrolizumab is the first time that the FDA has approved a cancer treatment for an indication based on TMB, and the fourth based on the presence of a biomarker rather than the primary site of origin.

Semiparametric odds rate model for modeling short-term and long-term effects with application to a breast cancer genetic study.

The proportional odds model is commonly used in the analysis of failure time data. The assumption of constant odds ratios over time in the proportional odds model, however, can be violated in some applications. Motivated by a genetic study with breast cancer patients, we propose a novel semiparametric odds rate model for the analysis of right-censored survival data. The proposed model incorporates the short-term and long-term covariate effects on the failure time data and includes the proportional odds model as a nested model. We develop efficient likelihood-based inference procedures and establish the large sample properties of the proposed nonparametric maximum likelihood estimators. Simulation studies demonstrate that the proposed methods perform well in practical settings. An application to the motivating example is provided.

Joint association analysis of bivariate quantitative and qualitative traits.

Univariate genome-wide association analysis of quantitative and qualitative traits has been investigated extensively in the literature. In the presence of correlated phenotypes, it is more intuitive to analyze all phenotypes simultaneously. We describe an efficient likelihood-based approach for the joint association analysis of quantitative and qualitative traits in unrelated individuals. We assume a probit model for the qualitative trait, under which an unobserved latent variable and a prespecified threshold determine the value of the qualitative trait. To jointly model the quantitative and qualitative traits, we assume that the quantitative trait and the latent variable follow a bivariate normal distribution. The latent variable is allowed to be correlated with the quantitative phenotype. Simultaneous modeling of the quantitative and qualitative traits allows us to make more precise inference on the pleiotropic genetic effects. We derive likelihood ratio tests for the testing of genetic effects. An application to the Genetic Analysis Workshop 17 data is provided. The new method yields reasonable power and meaningful results for the joint association analysis of the quantitative trait Q1 and the qualitative trait disease status at SNPs with not too small MAF.