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Addressing challenges with real-world synthetic control arms to demonstrate the comparative effectiveness of Pralsetinib in non-small cell lung cancer

ABSTRACT: As advanced non-small cell lung cancer (aNSCLC) is being increasingly divided into rare oncogene-driven subsets, conducting randomised trials becomes challenging. Using real-world data (RWD) to construct control arms for single-arm trials provides an option for comparative data. However, non-randomised treatment comparisons have the potential to be biased and cause concern for decision-makers. Using the example of pralsetinib from a RET fusion-positive aNSCLC single-arm trial (NCT03037385), we demonstrate a relative survival benefit when compared to pembrolizumab monotherapy and pembrolizumab with chemotherapy RWD cohorts. Quantitative bias analyses show that results for the RWD-trial comparisons are robust to data missingness, potential poorer outcomes in RWD and residual confounding. Overall, the study provides evidence in favour of pralsetinib as a first-line treatment for RET fusion-positive aNSCLC. The quantification of potential bias performed in this study can be used as a template for future studies of this nature. Real-world data (RWD) based control arms provide an option to compare the effectiveness of single-arm trials. By performing multiple quantitative bias analyses to alleviate concerns about trial-RWD comparability, here the authors show that the RET inhibitor pralsetinib provides survival benefit in patients with RET fusion-positive non-small cell lung cancer from the ARROW single-arm trial, (NCT03037385) when compared to pembrolizumab monotherapy and pembrolizumab with chemotherapy RWD cohorts.

SUBMITTER: Popat S

PROVIDER: S-EPMC9205915 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Project description:BackgroundMatching Adjusted Indirect Comparison (MAIC) is a statistical method used to adjust for potential biases when comparing treatment effects between separate data sources, with aggregate data in one arm, and individual patients data in the other. However, acceptance of MAIC in health technology assessment (HTA) is challenging because of the numerous biases that can affect the estimates of treatment effects - especially with small sample sizes, increasing the risk of convergence issues. We suggest statistical approaches to address some of the challenges in supporting evidence from MAICs, applied to a case study.MethodsThe proposed approaches were illustrated with a case study comparing an integrated analysis of three single-arm trials of entrectinib with the French standard of care using the Epidemio-Strategy and Medical Economics (ESME) Lung Cancer Data Platform, in metastatic ROS1-positive Non-Small Cell Lung Cancer (NSCLC) patients. To obtain convergent models with balanced treatment arms, a transparent predefined workflow for variable selection in the propensity score model, with multiple imputation of missing data, was used. To assess robustness, multiple sensitivity analyses were conducted, including Quantitative Bias Analyses (QBA) for unmeasured confounders (E-value, bias plot), and for missing at random assumption (tipping-point analysis).ResultsThe proposed workflow was successful in generating satisfactory models for all sub-populations, that is, without convergence problems and with effectively balanced key covariates between treatment arms. It also gave an indication of the number of models tested. Sensitivity analyses confirmed the robustness of the results, including to unmeasured confounders. The QBA performed on the missing data allowed to exclude the potential impact of the missing data on the estimate of comparative effectiveness, even though approximately half of the ECOG Performance Status data were missing.ConclusionsTo the best of our knowledge, we present the first in-depth application of QBA in the context of MAIC. Despite the real-world data limitations, with this MAIC, we show that it is possible to confirm the robustness of the results by using appropriate statistical methods.Trial registrationNA.

Project description:ObjectiveTo emulate the GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) trial using real world data before its publication. GRADE directly compared second line glucose lowering drugs for their ability to lower glycated hemoglobin A1c (HbA1c).DesignObservational study.SettingOptumLabs® Data Warehouse (OLDW), a nationwide claims database in the US, 25 January 2010 to 30 June 2019.ParticipantsAdults with type 2 diabetes and HbA1c 6.8-8.5% while using metformin monotherapy, identified according to the GRADE trial specifications, who also used glimepiride, liraglutide, sitagliptin, or insulin glargine.Main outcome measuresThe primary outcome was time to HbA1c ≥7.0%. Secondary outcomes were time to HbA1c >7.5%, incident microvascular complications, incident macrovascular complications, adverse events, all cause hospital admissions, and all cause mortality. Propensity scores were estimated using the gradient boosting machine method, and inverse propensity score weighting was used to emulate randomization of the treatment groups, which were then compared using Cox proportional hazards regression.Results8252 people were identified (19.7% of adults starting the study drugs in OLDW) who met eligibility criteria for the GRADE trial (glimepiride arm=4318, liraglutide arm=690, sitagliptin arm=2993, glargine arm=251). The glargine arm was excluded from analyses owing to small sample size. Median times to HbA1c ≥7.0% were 442 days (95% confidence interval 394 to 480 days) for glimepiride, 764 (741 to not calculable) days for liraglutide, and 427 (380 to 483) days for sitagliptin. Liraglutide was associated with lower risk of reaching HbA1c ≥7.0% compared with glimepiride (hazard ratio 0.57, 95% confidence interval 0.43 to 0.75) and sitagliptin (0.55, 0.41 to 0.73). Results were consistent for the secondary outcome of time to HbA1c >7.5%. No significant differences were observed among treatment groups for the remaining secondary outcomes.ConclusionsIn this emulation of the GRADE trial, liraglutide was statistically significantly more effective at maintaining glycemic control than glimepiride or sitagliptin when added to metformin monotherapy. Generating timely evidence on medical treatments using real world data as a complement to prospective trials is of value.

Project description:BackgroundAvatrombopag has been approved in patients who have severe thrombocytopenia (<50 × 109/L) and chronic liver disease (CLD) while receiving invasive procedures. The real-world application and effectiveness of avatrombopag in the subgroup patients with liver cancer remain unknown.MethodsLiver cancer patients (including primary liver cancer and colorectal cancer liver metastasis) who had severe thrombocytopenia and received avatrombopag were retrospectively enrolled. Avatrombopag dose, peak and absolute platelet count increase, combination treatment with other thrombopoietic agents, responder (peak count ≥50 × 109/L with absolute increase ≥20 × 109/L) rate, and anticancer treatment effect were analyzed. Thrombosis and bleeding events were assessed.ResultsIn total, 93 patients were enrolled, with 72 and 21 in the CLD and non-CLD groups, respectively. Patients with CLD had hepatitis B or C, larger spleen volume, and a higher cirrhosis degree. Baseline platelet counts were similar between two groups (median, 37.0 × 109/L vs. 39.0 × 109/L; P=0.594), while patients without CLD had higher peak platelet (median, 134.0 × 109/L vs. 74.0 × 109/L; P=0.015) and absolute increase (median, 101.0 × 109/L vs. 41.0 × 109/L; P=0.020) after avatrombopag treatment. The responder rate was higher in patients without CLD (100% vs. 76.4%; P=0.010). Combined avatrombopag with other thrombopoietic agents significantly increased platelet count; repeated use of avatrombopag produced similar effects with that of initial treatment. Concerning anticancer treatment effect, patients who responded to avatrombopag had a higher disease control rate. No thrombosis or hemorrhagic events were observed, even in patients with portal vein tumor thrombosis.ConclusionAvatrombopag was safe and effective and ensured successful implementation of anticancer treatment in liver cancer patients with severe thrombocytopenia, accompanied with or without CLD.

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Addressing challenges with real-world synthetic control arms to demonstrate the comparative effectiveness of Pralsetinib in non-small cell lung cancer

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