Effect of Crossover in Oncology Clinical Trials on Evidence Levels in Early Benefit Assessment in Germany

Isbary, Georg; Staab, Thomas R.; Amelung, Volker Eric; Dintsios, Charalabos-Markos; Iking‐Konert, Christof; Nesurini, Sonja Mariotti; Walter, Miriam; Ruof, Jörg

doi:10.1016/j.jval.2017.09.010

Cited by 12 publications

(6 citation statements)

References 29 publications

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“…Discordance between PFS and OS was previously reported in trials of NSCLC, as well as other solid tumors [ 3 , 23 , 24 ]. The effects of patients’ crossover in RCTs, as well as the different treatments used after the failure of experimental therapy in the trial, may certainly influence the OS results [ 25 ]. However, we think that results from this analysis should generate further confrontation and discussion in communities of clinicians and scientists.…”

Section: Discussionmentioning

confidence: 99%

Analysis of phase III clinical trials in metastatic NSCLC to assess the correlation between QoL results and survival outcomes

Servetto

Maïo

Salomone

et al. 2023

BMC Med

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Background In addition to improving survival outcomes, new oncology treatments should lead to amelioration of patients’ quality of life (QoL). Herein, we examined whether QoL results correlated with PFS and OS outcomes in phase III randomized controlled trials (RCTs) investigating new systemic treatments in metastatic non-small cell lung cancer (NSCLC). Methods The systematic search of PubMed was conducted in October 2022. We identified 81 RCTs testing novel drugs in metastatic NSCLC and published in the English language in a PubMed-indexed journal between 2012 and 2021. Only trials reporting QoL results and at least one survival outcome between OS and PFS were selected. For each RCT, we assessed whether global QoL was “superior,” “inferior,” or with “non-statistically significant difference” in the experimental arm compared to the control arm. Results Experimental treatments led to superior QoL in 30 (37.0%) RCTs and inferior QoL in 3 (3.7%) RCTs. In the remaining 48 (59.3%) RCTs, a statistically significant difference between the experimental and control arms was not found. Of note, we found a statistically significant association between QoL and PFS improvements (X2 = 3.93, p = 0.0473). In more detail, this association was not significant in trials testing immunotherapy or chemotherapy. On the contrary, in RCTs testing target therapies, QoL results positively correlated with PFS outcomes (p = 0.0196). This association was even stronger in the 32 trials testing EGFR or ALK inhibitors (p = 0.0077). On the other hand, QoL results did not positively correlate with OS outcomes (X2 = 0.81, p = 0.368). Furthermore, we found that experimental treatments led to superior QoL in 27/57 (47.4%) trials with positive results and in 3/24 (12.5%) RCTs with negative results (p = 0.0028). Finally, we analyzed how QoL data were described in publications of RCTs in which QoL outcomes were not improved (n = 51). We found that a favorable description of QoL results was associated with sponsorship by industries (p = 0.0232). Conclusions Our study reveals a positive association of QoL results with PFS outcomes in RCTs testing novel treatments in metastatic NSCLC. This association is particularly evident for target therapies. These findings further emphasize the relevance of an accurate assessment of QoL in RCTs in NSCLC.

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Section: Discussionmentioning

confidence: 99%

Analysis of phase III clinical trials in metastatic NSCLC to assess the correlation between QoL results and survival outcomes

Servetto

Maïo

Salomone

et al. 2023

BMC Med

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“…With the term study designs, we refer explicitly to the way the intervention arm is implemented in comparison to the control arm of the study. Other important factors with regard to design in oncology studies like endpoint operationalization [15,33], study duration or cross-over [34] are captured by the granted added benefit.…”

Section: Discussionmentioning

confidence: 99%

The impact of additive or substitutive clinical study design on the negotiated reimbursement for oncology pharmaceuticals after early benefit assessment in Germany

Dintsios

Beinhauer

2020

Health Econ Rev

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Background: We analysed the impact of clinical study design for oncological pharmaceuticals on the subsequent price negotiations after early benefit assessment between pharmaceutical companies and the German National Association of Statutory Health Insurance Funds. The analysis was conducted for all oncology pharmaceuticals that underwent the early benefit assessment in Germany since its introduction in 2011 up to September 2016. Methods: It was differentiated between additive (new therapy in addition to baseline therapy) and substitutive study designs (baseline therapy to be replaced). The study design was derived from the dossiers of the pharmaceutical companies submitted to the Federal Joint Committee. Subgroup specific costs in case of granted added benefit were calculated as annual therapy costs and compared with the costs of the appropriate comparators to quantify price premiums. Further price influencing factors were analysed in univariate and multivariate regression analysis considering the budget impact for the statutory health insurance as well. Results: The mean and the median of the additive premiums for substitutive designs (€50,477.68 and €49,841.24) were higher than for additive designs, if the comparator was different to best supportive care (€48,750.00 and €42,820.44). The mean multiplicative premium for the substitutive designs was 15.07 versus 2.29 for the additive designs. EU-Prices and target population size had a significant effect on the reimbursement. The adjusted R-square in the log Premium OLS-regressions reached 0.708 when including all explanatory variables and considering interaction between target population and annual costs of the comparator.

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“…Crossover trials (Figure 14) are another example requiring careful consideration of the data-generating processes induced by the RCT design to ensure that OS estimates are not misleading [203]. In crossover trials, patients initially assigned to the control arm can be given investigational therapy after the first disease progression [204]. The justification may be ethical, to not deprive patients of potentially helpful therapy, or to prevent patient dropout from the RCT.…”

Section: Intermediate Endpoints and Overall Survivalmentioning

confidence: 99%

Interpreting Randomized Controlled Trials

Msaouel,

Lee,

Thall

2023

Cancers

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This article describes rationales and limitations for making inferences based on data from randomized controlled trials (RCTs). We argue that obtaining a representative random sample from a patient population is impossible for a clinical trial because patients are accrued sequentially over time and thus comprise a convenience sample, subject only to protocol entry criteria. Consequently, the trial’s sample is unlikely to represent a definable patient population. We use causal diagrams to illustrate the difference between random allocation of interventions within a clinical trial sample and true simple or stratified random sampling, as executed in surveys. We argue that group-specific statistics, such as a median survival time estimate for a treatment arm in an RCT, have limited meaning as estimates of larger patient population parameters. In contrast, random allocation between interventions facilitates comparative causal inferences about between-treatment effects, such as hazard ratios or differences between probabilities of response. Comparative inferences also require the assumption of transportability from a clinical trial’s convenience sample to a targeted patient population. We focus on the consequences and limitations of randomization procedures in order to clarify the distinctions between pairs of complementary concepts of fundamental importance to data science and RCT interpretation. These include internal and external validity, generalizability and transportability, uncertainty and variability, representativeness and inclusiveness, blocking and stratification, relevance and robustness, forward and reverse causal inference, intention to treat and per protocol analyses, and potential outcomes and counterfactuals.

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Effect of Crossover in Oncology Clinical Trials on Evidence Levels in Early Benefit Assessment in Germany

Cited by 12 publications

References 29 publications

Analysis of phase III clinical trials in metastatic NSCLC to assess the correlation between QoL results and survival outcomes

Analysis of phase III clinical trials in metastatic NSCLC to assess the correlation between QoL results and survival outcomes

The impact of additive or substitutive clinical study design on the negotiated reimbursement for oncology pharmaceuticals after early benefit assessment in Germany

Interpreting Randomized Controlled Trials

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