FDA Approval Summary: Enfortumab Vedotin plus Pembrolizumab for Cisplatin-Ineligible Locally Advanced or Metastatic Urothelial Carcinoma.

On April 3, 2023, the FDA granted accelerated approval to enfortumab vedotin-ejfv (EV) plus pembrolizumab for treatment of patients with locally advanced or metastatic urothelial carcinoma who are ineligible for cisplatin-containing chemotherapy. Substantial evidence of effectiveness was obtained from EV-103/KEYNOTE-869 (NCT03288545), a multicohort study. Across cohorts, a total of 121 patients received EV 1.25 mg/kg (maximum of 125 mg) intravenously on days 1 and 8 of a 21-day cycle plus pembrolizumab 200 mg intravenously on day 1 of each 21-day cycle until disease progression or unacceptable toxicity. The major efficacy outcome measures were objective response rate (ORR) and duration of response (DoR), determined by blinded independent central review using RECIST v1.1. The confirmed ORR in 121 patients was 68% (95% confidence interval, 59-76), including 12% with complete responses. The median DoR for the 82 responders was 22 months (range: 1+ to 46+). The safety profile of the combination comprised adverse reactions expected to occur with the corresponding monotherapies, but with overall increased frequency of adverse reactions, including skin toxicity, pneumonitis, and peripheral neuropathy. The article summarizes the data and the FDA thought process supporting accelerated approval of EV + pembrolizumab, as well as additional exploratory analyses conducted by the FDA.

Regulatory implications of ctDNA in immuno-oncology for solid tumors.

In the era of precision oncology, use of circulating tumor DNA (ctDNA) is emerging as a minimally invasive approach for the diagnosis and management of patients with cancer and as an enrichment tool in clinical trials. In recent years, the US Food and Drug Administration has approved multiple ctDNA-based companion diagnostic assays for the safe and effective use of targeted therapies and ctDNA-based assays are also being developed for use with immuno-oncology-based therapies. For early-stage solid tumor cancers, ctDNA may be particularly important to detect molecular residual disease (MRD) to support early implementation of adjuvant or escalated therapy to prevent development of metastatic disease. Clinical trials are also increasingly using ctDNA MRD for patient selection and stratification, with an ultimate goal of improving trial efficiency through use of an enriched patient population. Standardization and harmonization of ctDNA assays and methodologies, along with further clinical validation of ctDNA as a prognostic and predictive biomarker, are necessary before ctDNA may be considered as an efficacy-response biomarker to support regulatory decision making.

FDA Approval Summary: Ribociclib Indicated for Male Patients with Hormone Receptor-Positive, HER2-Negative Advanced or Metastatic Breast Cancer.

On December 10, 2021, the FDA expanded the indications for ribociclib to include male patients for the treatment of hormone receptor-positive, HER2-negative advanced or metastatic breast cancer. Ribociclib is now indicated in combination with an aromatase inhibitor (AI) as initial endocrine-based therapy in adult patients, or with fulvestrant as initial endocrine-based therapy or following disease progression on endocrine therapy (ET), in postmenopausal women or in men. The efficacy of ribociclib + AI for male patients was primarily based on previous favorable benefit-risk assessments of ribociclib from MONALEESA-2 and MONALEESA-7 trials, and supported by COMPLEEMENT-1, an open-label, single-arm, multicenter clinical trial, in which 39 male patients (n = 3,246 total patients) received ribociclib + letrozole + goserelin/leuprolide. The overall response rate (ORR) based on confirmed responses in male patients with measurable disease at baseline was 46.9% [95% confidence interval (CI), 29.1-65.3], consistent with an ORR of 43.6% (95% CI, 41.5-45.8) in the overall population. Overall, adverse reactions occurring in male patients were similar to those occurring in female patients treated with ribociclib + ET. The efficacy of ribociclib + fulvestrant for male patients was primarily based on the previous findings of a favorable benefit-risk assessment from the MONALEESA-3 trial, supported by FDA review of clinical data of a limited number of male patients treated in clinical practice receiving ribociclib + fulvestrant. The known mechanism of action, biologic rationale, and clinical information available adequately demonstrate that the efficacy and safety of ribociclib + AI/fulvestrant are similar in male and female patients. This article summarizes the FDA's decision-making and data supporting the approval of ribociclib in male patients with breast cancer, and discusses regulatory insights.

Inferring species-level phylogenies and taxonomic distinctiveness using multilocus data in Sistrurus rattlesnakes.

Phylogenetic relationships and taxonomic distinctiveness of closely related species and subspecies are most accurately inferred from data derived from multiple independent loci. Here, we apply several approaches for understanding species-level relationships using data from 18 nuclear DNA loci and 1 mitochondrial DNA locus within currently described species and subspecies of Sistrurus rattlesnakes. Collectively, these methods provide evidence that a currently described species, the massasauga rattlesnake (Sistrurus catenatus), consists of two well-supported clades, one composed of the two western subspecies (S. c. tergeminus and S. c. edwardsii) and the other the eastern subspecies (S. c. catenatus). Within pigmy rattlesnakes (S. miliarius), however, there is not strong support across methods for any particular grouping at the subspecific level. Monophyly based tests for taxonomic distinctiveness show evidence for distinctiveness of all subspecies but this support is strongest by far for the S. c. catenatus clade. Because support for the distinctiveness of S. c. catenatus is both strong and consistent across methods, and due to its morphological distinctiveness and allopatric distribution, we suggest that this subspecies be elevated to full species status, which has significant conservation implications. Finally, most divergence time estimates based upon a fossil-calibrated species tree are > 50% younger than those from a concatenated gene tree analysis and suggest that an active period of speciation within Sistrurus occurred within the late Pliocene/Pleistocene eras.

FDA Approval Summary: Belzutifan for von Hippel-Lindau Disease-Associated Tumors.

On August 13, 2021, the FDA approved belzutifan (WELIREG, Merck), a first-in-class hypoxia-inducible factor (HIF) inhibitor for adult patients with von Hippel-Lindau (VHL) disease who require therapy for associated renal cell carcinoma (RCC), central nervous system (CNS) hemangioblastomas, or pancreatic neuroendocrine tumors (pNET), not requiring immediate surgery. The FDA granted approval based on the clinically meaningful effects on overall response rate (ORR) observed in patients enrolled in Study MK-6482-004. All 61 patients had VHL-associated RCC; some also had CNS hemangioblastomas and/or pNET. For VHL disease-associated RCC, ORR was 49% [95% confidence interval (CI), 36-62], median duration of response (DoR) was not reached, 56% of responders had DoR ≥12 months, and median time to response was 8 months. Twenty-four patients had measurable CNS hemangioblastomas with an ORR of 63% (95% CI, 41-81), and 12 patients had measurable pNET with an ORR of 83% (95% CI, 52-98). For these tumors, median DoR was not reached, with 73% and 50% of patients having response durations ≥12 months for CNS hemangioblastomas and pNET, respectively. The most common adverse reactions, including laboratory abnormalities, reported in ≥20% were anemia, fatigue, increased creatinine, headache, dizziness, increased glucose, and nausea. Belzutifan can render some hormonal contraceptives ineffective and can cause embryo-fetal harm during pregnancy. This article summarizes the data and the FDA thought process supporting traditional approval of belzutifan for this indication.

U.S. FDA Drug Approvals for Gynecological Malignancies: A Decade in Review.

Over the last decade, there has been tremendous progress in the treatment of patients with gynecologic cancers with a changing therapy landscape. This summary provides an overview of U.S. Food and Drug Administration (FDA) approvals for gynecologic cancers from 2010 to 2020, totaling 17 new indications. For each of the approved indications, endpoints, trial design, results, and regulatory considerations are outlined. Among these 17 indications, six received accelerated approval (AA) and 11 received regular approval (RA). As of September 2021, of the six AA, three have subsequently demonstrated clinical benefit resulting in conversion to RA and the remaining three have ongoing clinical trials that have not yet reported results. Approval decisions for these 17 indications were supported by primary efficacy endpoints of progression-free survival (n = 10), objective response rate (n = 6), and overall survival (n = 1) and showed a favorable benefit-risk profile. Among the 17 indications, 15 received priority review and three applications participated in one or more novel Oncology Center of Excellence initiatives, including Real Time Oncology Review, Assessment Aid, and Project Orbis. Current FDA thinking on drug development opportunities and regulatory initiatives currently under way will be discussed.

U.S. FDA Drug Approvals for Breast Cancer: A Decade in Review.

Over the last decade, the treatment of patients with breast cancer has been greatly impacted by the approval of multiple drugs and indications. This summary describes 30 FDA approvals of treatments for breast cancer from 2010 to 2020. The trial design endpoints, results, and regulatory considerations are described for each approved indication. Of the 30 indications, 23 (76.6%) received regular and 7 (23.3%) received accelerated approval. Twenty-six approvals were granted in metastatic breast cancer (MBC) and four in early breast cancer. Approval decisions for the 26 MBC indications were initially supported by progression-free survival (PFS) in 21 (80.8%), overall survival (OS) or a combination of OS and PFS in two (7.7%), and objective response rate (ORR) in three (11.5%). The four approvals in early breast cancer utilized pathologic complete response (pCR) in one (25%) and invasive disease-free survival (iDFS) in three (75%) trials. Among the 30 indications, 22 received priority review, seven were granted Breakthrough Therapy Designation, and 10 applications participated in one or more pilot Oncology Center of Excellence regulatory review initiatives, including Real Time Oncology Review, Assessment Aid, and Project Orbis. FDA initiatives to advance breast cancer drug development are also described.

Unifying vertical and nonvertical evolution: a stochastic ARG-based framework.

Evolutionary biologists have introduced numerous statistical approaches to explore nonvertical evolution, such as horizontal gene transfer, recombination, and genomic reassortment, through collections of Markov-dependent gene trees. These tree collections allow for inference of nonvertical evolution, but only indirectly, making findings difficult to interpret and models difficult to generalize. An alternative approach to explore nonvertical evolution relies on phylogenetic networks. These networks provide a framework to model nonvertical evolution but leave unanswered questions such as the statistical significance of specific nonvertical events. In this paper, we begin to correct the shortcomings of both approaches by introducing the "stochastic model for reassortment and transfer events" (SMARTIE) drawing upon ancestral recombination graphs (ARGs). ARGs are directed graphs that allow for formal probabilistic inference on vertical speciation events and nonvertical evolutionary events. We apply SMARTIE to phylogenetic data. Because of this, we can typically infer a single most probable ARG, avoiding coarse population dynamic summary statistics. In addition, a focus on phylogenetic data suggests novel probability distributions on ARGs. To make inference with our model, we develop a reversible jump Markov chain Monte Carlo sampler to approximate the posterior distribution of SMARTIE. Using the BEAST phylogenetic software as a foundation, the sampler employs a parallel computing approach that allows for inference on large-scale data sets. To demonstrate SMARTIE, we explore 2 separate phylogenetic applications, one involving pathogenic Leptospirochete and the other Saccharomyces.

FDA Approval Summary: Pertuzumab, Trastuzumab, and Hyaluronidase-zzxf Injection for Subcutaneous Use in Patients with HER2-positive Breast Cancer.

On June 29, 2020, the FDA approved pertuzumab, trastuzumab, and hyaluronidase-zzxf subcutaneous injection (Phesgo) for the treatment of patients with HER2-positive early-stage and metastatic breast cancer. Patients should be selected for therapy based on an FDA-approved companion diagnostic test. Approval was primarily based on the FeDeriCa trial, a randomized, open-label, multicenter comparability study of pertuzumab, trastuzumab, and hyaluronidase-zzxf subcutaneous injection compared with intravenous pertuzumab and intravenous trastuzumab administered in the neoadjuvant and adjuvant settings with chemotherapy for the treatment of patients with early breast cancer. The pharmacokinetic endpoints were, first, to demonstrate that the exposure of subcutaneous pertuzumab was not inferior to that of intravenous pertuzumab, and then to demonstrate that the exposure of subcutaneous trastuzumab was not inferior to that of intravenous trastuzumab. The primary endpoints were met with the observed lower limit of the two-sided 90% confidence intervals above the prespecified noninferiority margins. The most common adverse reactions were alopecia, nausea, diarrhea, anemia, and asthenia. The totality of the evidence demonstrated comparability of the subcutaneous product to intravenous, allowing for extrapolation and approval of all breast cancer indications for which intravenous trastuzumab and pertuzumab are approved.

Subgroup Analyses in Oncology Trials: Regulatory Considerations and Case Examples.

Subgroup analyses are assessments of treatment effects based on certain patient characteristics out of the total study population and are important for interpretation of pivotal oncology trials. However, appropriate use of subgroup analyses results for regulatory decision-making and product labeling is challenging. Typically, drugs approved by the FDA are indicated for use in the total patient population studied; however, there are examples of restriction to a subgroup of patients despite positive study results in the entire study population and also extension of an indication to the entire study population despite positive results appearing primarily in one or more subgroups. In this article, we summarize key issues related to subgroup analyses in the benefit-risk assessment of cancer drugs and provide case examples to illustrate approaches that the FDA Oncology Center of Excellence has taken when considering the appropriate patient population for cancer drug approval. In general, if a subgroup is of interest, the subgroup analysis should be hypothesis-driven and have adequate sample size to demonstrate evidence of a treatment effect. In addition to statistical efficacy considerations, the decision on what subgroups to include in labeling relies on the pathophysiology of the disease, mechanistic justification, safety data, and external information available. The oncology drug review takes the totality of the data into consideration during the decision-making process to ensure the indication granted and product labeling appropriately reflect the scientific evidence to support patient population for whom the drug is safe and effective.

StepBrothers: inferring partially shared ancestries among recombinant viral sequences.

Phylogeneticists have developed several statistical methods to infer recombination among molecular sequences that are evolutionarily related. Of these methods, Markov change-point models currently provide the most coherent framework. Yet, the Markov assumption is faulty in that the inferred relatedness of homologous sequences across regions divided by recombinant events is not independent, particularly for nonrecombinant sequences as they share the same history. To correct this limitation, we introduce a novel random tips (RT) model. The model springs from the idea that a recombinant sequence inherits its characters from an unknown number of ancestral full-length sequences, of which one only observes the incomplete portions. The RT model decomposes recombinant sequences into their ancestral portions and then augments each portion onto the data set as unique partially observed sequences. This data augmentation generates a random number of sequences related to each other through a single inferable tree with the same random number of tips. While intuitively pleasing, this single tree corrects the independence assumptions plaguing previous methods while permitting the detection of recombination. The single tree also allows for inference of the relative times of recombination events and generalizes to incorporate multiple recombinant sequences. This generalization answers important questions with which previous models struggle. For example, we demonstrate that a group of human immunodeficiency type 1 recombinant viruses from Argentina, previously thought to have the same recombinant history, actually consist of 2 groups: one, a clonal expansion of a reference sequence and another that predates the formation of the reference sequence. In another example, we demonstrate that 2 hepatitis B virus recombinant strains share similar splicing locations, suggesting a common descent of the 2 viruses. We implement and run both examples in a software package called StepBrothers, freely available to interested parties.

Regulatory Considerations for Contribution of Effect of Drugs Used in Combination Regimens: Renal Cell Cancer Case Studies.

The development and review of combination drug regimens in oncology may present unique challenges to investigators and regulators. For regulatory approval of combination regimens, it is necessary to demonstrate the contribution of effect of each monotherapy to the overall combination. Alternative approaches to traditional designs may be needed to accelerate oncology drug development, for example, when combinations are substantially superior to available therapy, to reduce exposure to less effective therapies, and for drugs that are inactive as single agents and that in combination potentiate activity of another drug. These approaches include demonstration of activity in smaller randomized trials and/or monotherapy trials conducted in a similar disease setting. This article will discuss alternative approaches used in the development of approved drugs in combination, based on examples of recent approvals of combination regimens in renal cell carcinoma.

Smooth skyride through a rough skyline: Bayesian coalescent-based inference of population dynamics.

Kingman's coalescent process opens the door for estimation of population genetics model parameters from molecular sequences. One paramount parameter of interest is the effective population size. Temporal variation of this quantity characterizes the demographic history of a population. Because researchers are rarely able to choose a priori a deterministic model describing effective population size dynamics for data at hand, nonparametric curve-fitting methods based on multiple change-point (MCP) models have been developed. We propose an alternative to change-point modeling that exploits Gaussian Markov random fields to achieve temporal smoothing of the effective population size in a Bayesian framework. The main advantage of our approach is that, in contrast to MCP models, the explicit temporal smoothing does not require strong prior decisions. To approximate the posterior distribution of the population dynamics, we use efficient, fast mixing Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. In a simulation study, we demonstrate that the proposed temporal smoothing method, named Bayesian skyride, successfully recovers "true" population size trajectories in all simulation scenarios and competes well with the MCP approaches without evoking strong prior assumptions. We apply our Bayesian skyride method to 2 real data sets. We analyze sequences of hepatitis C virus contemporaneously sampled in Egypt, reproducing all key known aspects of the viral population dynamics. Next, we estimate the demographic histories of human influenza A hemagglutinin sequences, serially sampled throughout 3 flu seasons.

Noninvasive diagnosis of cellular and antibody-mediated rejection by perforin and granzyme B in renal allografts.

A major milestone in transplantation would be the use of biomarkers to monitor rejection. We examined the association between perforin and granzyme-B gene expression detected in the peripheral blood of renal allograft recipients with cellular and antibody-mediated rejection. Furthermore, we judged the appropriateness of assigning negative rejection statuses to persons without a biopsy whose grafts were functioning well clinically. Of the 46 patients who completed the study, recipients with cellular rejection had higher perforin and granzyme-B levels compared with nonrejectors (p = 0.006). Interestingly, recipients with antibody-mediated rejection also had higher perforin and granzyme-B levels compared with nonrejectors (p = 0.04). Patients with high levels of granzyme B had a probability of rejecting that was 26.7 times greater than those patients with low levels of granzyme B. Perforin and granzyme B had sensitivities of 50% and specificities of 95% in predicting rejection (cutoff value = 140). Assigning negative rejection statuses to recipients without a biopsy whose grafts were functioning well did not have a major effect on the direction or significance of covariate values. This study suggests that perforin and granzyme-B gene expressions in peripheral blood are accurate in detecting both cellular and antibody-mediated rejection.

Three roads diverged? Routes to phylogeographic inference.

Phylogeographic methods facilitate inference of the geographical history of genetic lineages. Recent examples explore human migration and the origins of viral pandemics. There is longstanding disagreement over the use and validity of certain phylogeographic inference methodologies. In this paper, we highlight three distinct frameworks for phylogeographic inference to give a taste of this disagreement. Each of the three approaches presents a different viewpoint on phylogeography, most fundamentally on how we view the relationship between the inferred history of a sample and the history of the population the sample is embedded in. Satisfactory resolution of this relationship between history of the tree and history of the population remains a challenge for all but the most trivial models of phylogeographic processes. Intriguingly, we believe that some recent methods that entirely avoid inference about the history of the population will eventually help to reach a resolution.