Assessment-Schedule Matching in Unanchored Indirect Treatment Comparisons of Progression-Free Survival in Cancer Studies

Feasibility of Indirect Treatment Comparisons Between Niraparib Plus Abiraterone Acetate and Other First-Line Poly ADP-Ribose Polymerase Inhibitor Treatment Regimens for Patients with BRCA1/2 Mutation-Positive Metastatic Castration-Resistant Prostate Cancer

INTRODUCTION

Poly(ADP-ribose) polymerase inhibitors (PARPi) are a novel option to treat patients with metastatic castration-resistant prostate cancer (mCRPC). Niraparib plus abiraterone acetate and prednisone (AAP) is indicated for BRCA1/2 mutation-positive mCRPC. Niraparib plus AAP demonstrated safety and efficacy in the phase 3 MAGNITUDE trial (NCT03748641). In the absence of head-to-head studies comparing PARPi regimens, the feasibility of conducting indirect treatment comparisons (ITC) to inform decisions for patients with first-line BRCA1/2 mutation-positive mCRPC has been explored.

METHODS

A systematic literature review was conducted to identify evidence from randomized controlled trials on relevant comparators to inform the feasibility of conducting ITCs via network meta-analysis (NMA) or population-adjusted indirect comparisons (PAIC). Feasibility was assessed based on network connectivity, data availability in the BRCA1/2 mutation-positive population, and degree of within- and between-study heterogeneity or bias.

RESULTS

NMAs between niraparib plus AAP and other PARPi regimens (olaparib monotherapy, olaparib plus AAP, and talazoparib plus enzalutamide) were inappropriate due to the disconnected network, differences in trial populations related to effect modifiers, or imbalances within BRCA1/2 mutation-positive subgroups. The latter issue, coupled with the lack of a common comparator (except for olaparib plus AAP), also rendered anchored PAICs infeasible. Unanchored PAICs were either inappropriate due to lack of population overlap (vs. olaparib monotherapy) or were restricted by unmeasured confounders and small sample size (vs. olaparib plus AAP). PAIC versus talazoparib plus enzalutamide was not possible due to lack of published arm-level baseline characteristics and sufficient efficacy outcome data in the relevant population.

CONCLUSION

The current randomized controlled trial evidence network does not permit robust comparisons between niraparib plus AAP and other PARPi regimens for patients with 1L BRCA-positive mCRPC. Decision-makers should scrutinize any ITC results in light of their limitations. Real-world evidence combined with clinical experience should inform treatment recommendations in this indication.

Long-Term Comparative Efficacy and Safety of Risdiplam and Nusinersen in Children with Type 1 Spinal Muscular Atrophy

INTRODUCTION

Spinal muscular atrophy (SMA) is a severe genetic neuromuscular disease characterized by a loss of motor neurons and progressive muscle weakness. Children with untreated type 1 SMA never sit independently and require increasing levels of ventilatory support as the disease progresses. Without intervention, and lacking ventilatory support, death typically occurs before the age of 2 years. There are currently no head-to-head trials comparing available treatments in SMA. Indirect treatment comparisons are therefore needed to provide information on the relative efficacy and safety of SMA treatments for healthcare decision-making.

METHODS

The long-term efficacy and safety of risdiplam versus nusinersen in children with type 1 SMA was evaluated using indirect treatment comparison methodology to adjust for differences between population baseline characteristics, to reduce any potential bias in the comparative analysis. An unanchored matching-adjusted indirect comparison was conducted using risdiplam data from 58 children in FIREFISH (NCT02913482) and published aggregate nusinersen data from 81 children obtained from the ENDEAR (NCT02193074) and SHINE (NCT02594124) clinical trials with at least 36 months of follow-up.

RESULTS

Children with type 1 SMA treated with risdiplam had a 78% reduction in the rate of death, an 81% reduction in the rate of death or permanent ventilation, and a 57% reduction in the rate of serious adverse events compared with children treated with nusinersen. Children treated with risdiplam also had a 45% higher rate of achieving a Hammersmith Infant Neurological Examination, Module 2 motor milestone response and a 186% higher rate of achieving a ≥ 4-point improvement in Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders compared with children treated with nusinersen.

CONCLUSION

Long-term data supported risdiplam as a superior alternative to nusinersen in children with type 1 SMA. Video abstract available for this article. Video abstract (MP4 184542 KB).

Framework for the Use of External Controls to Evaluate Treatment Outcomes in Precision Oncology Trials

Advances in genomics have enabled anticancer therapies to be tailored to target specific genomic alterations. Single-arm trials (SATs), including those incorporated within umbrella, basket, and platform trials, are widely adopted when it is not feasible to conduct randomized controlled trials in rare biomarker-defined subpopulations. External controls (ECs), defined as control arm data derived outside the clinical trial, have gained renewed interest as a strategy to supplement evidence generated from SATs to allow comparative analysis. There are increasing examples demonstrating the application of EC in precision oncology trials. The prospective application of EC in conducting comparative studies is associated with distinct methodological challenges, the specific considerations for EC use in biomarker-defined subpopulations have not been adequately discussed, and a formal framework is yet to be established. In this review, we present a framework for conducting a prospective comparative analysis using EC. Key steps are (1) defining the purpose of using EC to address the study question, (2) determining if the external data are fit for purpose, (3) developing a transparent study protocol and a statistical analysis plan, and (iv) interpreting results and drawing conclusions on the basis of a prespecified hypothesis. We specify the considerations required for the biomarker-defined subpopulations, which include (1) specifying the comparator and biomarker status of the comparator group, (2) defining lines of treatment, (3) assessment of the biomarker testing panels used, and (4) assessment of cohort stratification in tumor-agnostic studies. We further discuss novel clinical trial designs and statistical techniques leveraging EC to propose future directions to advance evidence generation and facilitate drug development in precision oncology.

Modelling Health State Utilities as a Transformation of Time to Death in Patients with Non-Small Cell Lung Cancer

BACKGROUND

When utilities are analyzed by time to death (TTD), this has historically been implemented by 'grouping' observations as discrete time periods to create health state utilities. We extended the approach to use continuous functions, avoiding assumptions around groupings. The resulting models were used to test the concept with data from different regions and different country tariffs.

METHODS

Five-year follow-up in advanced non-small cell lung cancer (NSCLC) was used to fit six continuous TTD models using generalized estimating equations, which were compared with progression-based utilities and previously published TTD groupings. Sensitivity analyses were performed using only patients with a confirmed death, the last year of life only, and artificially censoring data at 24 months. The statistically best-fitting model was then applied to data subsets by region and different EQ-5D-3L country tariffs.

RESULTS

Continuous (natural) [Formula: see text] and [Formula: see text] models outperformed other continuous models, grouped TTD, and progression-based models in statistical fit (mean absolute error and Quasi Information Criterion). This held through sensitivity and scenario analyses. The pattern of reduced utility as a patient approaches death was consistent across regions and EQ-5D tariffs using the preferred [Formula: see text] model.

CONCLUSIONS

The use of continuous models provides a statistically better fit than TTD groupings, without the need for strong assumptions about the health states experienced by patients. Where a TTD approach is merited for use in modelling, continuous functions should be considered, with the scope for further improvements in statistical fit by both widening the number of candidate models tested and the therapeutic areas investigated.

An Indirect Comparison of the Efficacy and Safety of Dostarlimab and Doxorubicin for the Treatment of Advanced and Recurrent Endometrial Cancer

BACKGROUND

There is no clear standard of care for advanced/recurrent endometrial cancer (EC) following platinum-based therapy. Dostarlimab is approved for patients with mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) advanced/recurrent EC. This indirect treatment comparison (ITC) assessed dostarlimab efficacy and safety from the single-arm GARNET (NCT02715284) trial compared with doxorubicin from ZoptEC (NCT01767155).

PATIENTS AND METHODS

Patient-level data and study variables from GARNET Cohort A1 (dMMR/MSI-H EC) and the ZoptEC doxorubicin control arm were merged. Patients were matched based on eligibility criteria (main analysis population). Safety population included all patients who received treatment. The primary efficacy comparison outcome, overall survival (OS), was calculated using a Cox proportional hazards model, with adjusted stabilized inverse probability of treatment weighting. Modified assessment-scheduled matching Kaplan--Meier analysis was used for progression-free survival (PFS) and time to deterioration (TTD) in quality of life (QoL).

RESULTS

In the main analysis population, median (95% CI) OS was not reached (NR; 18.0 months--NR) for dostarlimab (n = 92) and was 11.2 (10.0-13.1) months for doxorubicin (n = 233; HR: 0.41 [95% CI: 0.28-0.61]); median PFS was 12.2 (3.3-NR) and 4.9 (4.1-6.6) months, respectively. Median TTD in QoL was NR (2.5-NR; n = 61) and 4.5 (4.1-5.4; n = 188) months, respectively. Similar rates of adverse events (AEs, 11.6% vs 15.3%) and serious AEs (34.1% vs 30.1%) were observed with dostarlimab (n = 129) and doxorubicin (n = 249). Grade ≥3 AEs occurred in 48.1% vs 78.3%, respectively.

CONCLUSION

This ITC suggests a favorable benefit:risk profile for dostarlimab in patients with dMMR/MSI-H advanced/recurrent EC.

Treatment effectiveness in a rare oncology indication: Lessons from an external control cohort study

Real-world data (RWD) reflecting patient treatment in routine clinical practice can be used to develop external control groups for single-arm trials. External controls can provide valuable benchmark results on potential comparator drug effectiveness, particularly in rare indications when randomized controlled trials are either infeasible or unethical. This paper describes lessons learned from a descriptive real-world external control cohort study conducted to provide benchmark data for a single-arm clinical trial in a rare oncology biomarker driven disease. Conducting external control cohort studies to evaluate treatment effectiveness in rare indications likely will present with data and analysis challenges as seen in the example study. However, there are mitigating measures that can be applied in the study design, identification of RWD sources, and data analysis. The lessons learned and reported here with a proposal of an external control study framework can provide guidance for future research in this area, and may be applicable as well in other rare indications. Taking these learnings into consideration, the use of real-world external controls to contextualize treatment effectiveness in rare indications is a valuable approach and warrants further application in the future.

Modeling Challenges in Cost-Effectiveness Analysis of First-Line Immuno-Oncology Therapies in Non-small Cell Lung Cancer: A Systematic Literature Review

INTRODUCTION

The introduction of immuno-oncology (IO) therapies has changed the treatment landscape of non-small cell lung cancer (NSCLC). Numerous cost-effectiveness analyses (CEAs) and technology appraisals (TAs) evaluating IO therapies have been recently published.

OBJECTIVE

We reviewed economic models of first-line (1L) IO therapies for previously untreated advanced or metastatic NSCLC to identify methodological challenges associated with modeling cost effectiveness from published literature and TAs and to make recommendations for future CEAs in this disease area.

METHODS

A systematic literature review was conducted following Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched MEDLINE, Embase, EconLit (January 2009-January 2020), and select conferences (since 2016) for CEAs of 1L IO treatments in patients with recurrent or metastatic, epidermal growth factor receptor (EGFR)/anaplastic lymphoma kinase (ALK) mutation-negative NSCLC, published in English. TAs from England, Scotland, Canada, Australia, Germany, and France were also examined. Two reviewers screened the results and extracted the data. The quality of the CEAs was described using the Drummond checklist.

RESULTS

In total, 46 records reporting on 38 unique models met protocol-defined criteria and were included. Five models adjusted for treatment switching or crossover in base-case analyses, and the remainder considered treatment switching or crossover to represent clinical practice and made no adjustment. Seven models used external real-world data for survival modeling or extrapolation validation. Six models that assumed long-term treatment benefit stopped at 3 or 5 years after initiation. Seven models used the observed time-on-treatment distribution from the trial, and eight used progression-free survival for treatment duration. All models compared one or more IO monotherapies or combination therapies with chemotherapy. Only one study directly compared different IO agents but did not consider the concordance issue across programmed death-ligand 1 (PD-L1) testing methods. Utilities were modeled by health state in 12 models, four applied a time-to-death approach, and ten explored both. None applied cure models.

CONCLUSION

Variations in methodological challenges were seen across studies. Previous models took approaches that were followed in subsequent models, such as a 2-year stopping rule of IO duration or treatment-effect waning. Challenges such as heterogeneity in PD-L1 testing and survival extrapolation and validation using real-world data should be further considered for future models in advanced or metastatic NSCLC.

Bridging the divide between clinical research and clinical care in oncology: An integrated real-world evidence generation platform

Real world data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources; real-world evidence (RWE) generated by RWD analyses can become an important component of drug development programs and, potentially, regulatory decision-making. As a RWD source, electronic health records (EHRs) can now provide patient-level data at unparalleled depth and granularity. We propose a RWE generation framework that could maximize the synergy between RWD and prospective clinical trials by capitalizing on an emerging data curation infrastructure that may be applied to both retrospective and prospective research. In this platform, centralized data collection and monitoring could be enabled via routine EHR use, and seamlessly integrated with select intentional data capture during prospective study periods. By bridging the divide between routine care and clinical research, this integrated platform aggregates retrospective and prospective data, collected both routinely and intentionally. This approach makes clinical trial participation more available to patients, increasing the potential depth of data, representativeness and efficiency of clinical research.

DREAMM-2: Indirect Comparisons of Belantamab Mafodotin vs. Selinexor + Dexamethasone and Standard of Care Treatments in Relapsed/Refractory Multiple Myeloma

Introduction

Single-agent belantamab mafodotin (belamaf; BLENREP) demonstrated deep and durable responses in patients with relapsed/refractory multiple myeloma and ≥ 3 prior lines of therapy, including an immunomodulatory agent, proteasome inhibitor, and anti-CD38 antibody (DREAMM-2; NCT03525678).

Methods

At the time of this study, STORM Part 2, NCT02336815 (selinexor plus low-dose dexamethasone; sel + dex) was systematically identified as the only feasible comparator to the DREAMM-2 cohort. Matching-adjusted indirect comparisons (MAIC) evaluated efficacy and safety of belamaf (2.5 mg/kg; n = 97) versus sel + dex (80 mg + 20 mg, respectively; n = 123). Populations were weighted for clinically validated effect modifiers and prognostic factors. Outcomes included overall survival (OS), progression-free survival (PFS), duration of response (DoR), overall response rate (ORR), time to response (TTR), and safety. The relative efficacy of belamaf versus standard of care (SoC) on OS was estimated by a Bucher indirect treatment comparison using the MAIC-adjusted hazard ratios (HR) for OS of belamaf (DREAMM-2) versus sel + dex (STORM Part 2) and a HR adjusted for refractoriness to carfilzomib and high-risk cytogenetics of sel + dex (STORM) versus SoC (MAMMOTH).

Results

Belamaf demonstrated improved OS (HR 0.53; 95% confidence interval 0.34, 0.83; p = 0.005) and DoR (0.41; 0.21, 0.83; p = 0.013) versus sel + dex. There were no statistically significant differences in ORR, TTR, and PFS. Belamaf had a favorable safety profile for most evaluable hematologic (any-grade, Grade 3–4) and non-hematologic (any-grade) adverse events versus sel + dex. Significantly improved OS was observed with belamaf versus SoC (0.29; 0.16, 0.54; p < 0.001).

Conclusion

Single-agent belamaf represents a new treatment option for triple-class refractory patients with RRMM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-021-01884-7.

Population-adjusted indirect treatment comparison of maintenance PARP inhibitor with or without bevacizumab versus bevacizumab alone in women with newly diagnosed advanced ovarian cancer

BACKGROUND

In patients with newly diagnosed ovarian cancer, bevacizumab and poly(ADP-ribose) polymerase (PARP) inhibitors, alone or in combination, have shown benefit as maintenance treatment following platinum-based chemotherapy. However, no trials have compared a PARP inhibitor plus bevacizumab versus a PARP inhibitor, or a PARP inhibitor versus bevacizumab. We performed an unanchored population-adjusted indirect treatment comparison to estimate the relative efficacy and safety of maintenance treatments for newly diagnosed advanced ovarian cancer.

METHODS

Analyses were performed using aggregate data from the PRIMA trial and patient-level data from a subset of patients from the PAOLA-1 trial that met surgery and staging eligibility criteria of PRIMA. Propensity weights were used to match baseline characteristics of the PAOLA-1 subset to those of the PRIMA population. Analysis was performed in overall (biomarker-unselected) and homologous recombination repair deficiency (HRD)-positive populations.

RESULTS

A total of 595/806 (266/387 HRD-positive) PAOLA-1 patients were included. After matching, the effective sample size for PAOLA-1 was 532 (242 HRD-positive). Maintenance olaparib plus bevacizumab reduced the risk of disease progression or death by 43% [hazard ratio (HR) 0.57; 95% confidence interval (CI): 0.47-0.69] versus niraparib and by 40% (HR 0.60; 95% CI: 0.49-0.74) versus bevacizumab in the biomarker-unselected population and by 43% (HR 0.57; 95% CI: 0.41-0.79) and 60% (HR 0.40; 95% CI: 0.29-0.55), respectively, in the HRD-positive population. Progression-free survival (PFS) benefits of maintenance niraparib and bevacizumab arms were comparable in the biomarker-unselected population (HR 1.07; 95% CI: 0.87-1.32); however, niraparib showed a 30% reduced risk compared with bevacizumab (HR 0.70; 95% CI: 0.51-0.97) in the HRD-positive population.

CONCLUSIONS

In biomarker-unselected and HRD-positive patients, combination treatment with olaparib plus bevacizumab as maintenance treatment improves PFS for women with newly diagnosed advanced ovarian cancer compared with either bevacizumab or niraparib alone. Results are hypothesis generating and could guide randomised trial design.

How Assessment-Schedule Matching Limits Bias When Comparing Progression-Free Survival in Single-Arm Studies: An Application in Second-Line Urothelial Carcinoma Treatments

OBJECTIVES

Population-adjusted comparisons of progression-free survival (PFS) from single-arm trials of cancer treatments can be derived using matching-adjusted indirect comparisons (MAICs); however, results are still susceptible to bias, particularly if the trials had different tumor assessment schedules. This study aims to assess the effects of assessment-schedule matching (ASM) on the relative effectiveness on the PFS of avelumab versus approved comparator immunotherapies or chemotherapy after population matching in the second-line (2L) setting for metastatic urothelial carcinoma.

METHODS

The MAIC used patient-level data for avelumab from the JAVELIN Solid Tumor trial (NCT01772004). PFS was compared with published curves for other treatments to obtain population-adjusted hazard ratios (HRs). The MAIC was repeated after conducting ASM for differences in tumor assessment scheduled first at 6 weeks for avelumab and durvalumab and at 8 or 9 weeks for other treatments.

RESULTS

MAIC adjustment alone altered the HR estimates up to 23%, whereas MAIC plus ASM resulted in up to 32.7% reductions from naive comparisons. Even in cases in which MAIC had little effect, ASM brought an additional change of 11.1% to 15.4%. Overall, the HR range of avelumab versus other treatments changed from 0.83 to 1.25 for naive comparisons to 0.76 to 0.99 after ASM plus MAIC, numerically favoring avelumab.

CONCLUSIONS

Small variations in assessment schedules can introduce bias in unanchored indirect treatment comparisons of interval-censored time-to-event outcomes. In this study, adjusted PFS was comparable across second-line urothelial carcinoma treatment options, numerically favoring avelumab versus immunotherapies and chemotherapy agents. Correcting this bias is especially important when HRs are applied in cost-effectiveness models to transition patients between states.

Differential frequency in imaging-based outcome measurement: Bias in real-world oncology comparative-effectiveness studies

Background

Comparative‐effectiveness studies using real‐world data (RWD) can be susceptible to surveillance bias. In solid tumor oncology studies, analyses of endpoints such as progression‐free survival (PFS) are based on progression events detected by imaging assessments. This study aimed to evaluate the potential bias introduced by differential imaging assessment frequency when using electronic health record (EHR)‐derived data to investigate the comparative effectiveness of cancer therapies.

Methods

Using a nationwide de‐identified EHR‐derived database, we first analyzed imaging assessment frequency patterns in patients diagnosed with advanced non‐small cell lung cancer (aNSCLC). We used those RWD inputs to develop a discrete event simulation model of two treatments where disease progression was the outcome and PFS was the endpoint. Using this model, we induced bias with differential imaging assessment timing and quantified its effect on observed versus true treatment effectiveness. We assessed percent bias in the estimated hazard ratio (HR).

Results

The frequency of assessments differed by cancer treatment types. In simulated comparative‐effectiveness studies, PFS HRs estimated using real‐world imaging assessment frequencies differed from the true HR by less than 10% in all scenarios (range: 0.4% to −9.6%). The greatest risk of biased effect estimates was found comparing treatments with widely different imaging frequencies, most exaggerated in disease settings where time to progression is very short.

Conclusions

This study provided evidence that the frequency of imaging assessments to detect disease progression can differ by treatment type in real‐world patients with cancer and may induce some bias in comparative‐effectiveness studies in some situations.

Progression-free survival in oncological clinical studies: Assessment time bias and methods for its correction

Progression-free survival (PFS) is a frequently used endpoint in oncological clinical studies. In case of PFS, potential events are progression and death. Progressions are usually observed delayed as they can be diagnosed not before the next study visit. For this reason potential bias of treatment effect estimates for progression-free survival is a concern. In randomized trials and for relative treatment effects measures like hazard ratios, bias-correcting methods are not necessarily required or have been proposed before. However, less is known on cross-trial comparisons of absolute outcome measures like median survival times. This paper proposes a new method for correcting the assessment time bias of progression-free survival estimates to allow a fair cross-trial comparison of median PFS. Using median PFS for example, the presented method approximates the unknown posterior distribution by a Bayesian approach based on simulations. It is shown that the proposed method leads to a substantial reduction of bias as compared to estimates derived from maximum likelihood or Kaplan-Meier estimates. Bias could be reduced by more than 90% over a broad range of considered situations differing in assessment times and underlying distributions. By coverage probabilities of at least 94% based on the credibility interval of the posterior distribution the resulting parameters hold common confidence levels. In summary, the proposed approach is shown to be useful for a cross-trial comparison of median PFS.