In its original submission, the company pooled chemotherapy outcomes from SPOTLIGHT, GLOW, and CheckMate 649 to estimate the outcomes in the chemotherapy arm. The company explained that including CheckMate 649 increased the sample size and follow up, because CheckMate 649 has a median follow up of 4 years. It added that because CheckMate 649 has a longer follow up, it would capture the tails of the Kaplan–Meier curves, which would have smaller patient numbers with shorter follow up. The company added that in TA857, CheckMate 649 was considered generalisable to the NHS, so including it adds more power to the extrapolation. The company recreated individual patient-level data from CheckMate 649 by digitising the survival curves using an algorithm by Guyot et al. (2012). Then, patient-level data from CheckMate 649, SPOTLIGHT and GLOW was combined into a single dataset. The company did not adjust for patient characteristics and expected any numerical differences in survival outcomes to be caused by chance and variability in trial populations. The company also assumed equivalent efficacy for chemotherapy regimens, that is, the choice of chemotherapy regimen would not affect survival outcomes. The company added that its OS extrapolation for chemotherapy is supported by real-world evidence. It highlighted that in TA857, a small proportion of people were alive at 5 years and beyond, which suggests that long-term survival is plausible for people having chemotherapy. The EAG highlighted the methodological uncertainty of naive pooling of chemotherapy outcomes by not adjusting for differences in patient characteristics and using recreated data from CheckMate 649. So, the EAG excluded CheckMate 649 in its base case. At the first committee meeting, the committee considered that there were benefits to including evidence from CheckMate 649 as part of the chemotherapy arm. But, it highlighted that naive pooling added to uncertainty. It suggested that the company should explore the feasibility and appropriateness of using other methods to include more mature evidence from CheckMate 649 in the survival outcomes for chemotherapy. For example, using data from CheckMate 649 to derive an informative prior for the shape parameters of extrapolation models based on SPOTLIGHT and GLOW. The committee noted that, although CheckMate 649 has a longer follow up, it also has low patient numbers at the tails of the Kaplan–Meier curves, which adds uncertainty.
In response to the draft guidance consultation, the company provided evidence comparing its OS extrapolations with survival in external cohorts. The company stated that its OS extrapolation was more aligned with external cohort estimates of OS at 5 years, than the EAGs. As suggested by committee, the company also used data from CheckMate 649 to derive an informative prior. The log-logistic model was selected by the company to model CheckMate 649 OS for chemotherapy. The shape parameter of this model was used as the informative prior for the company's chemotherapy OS extrapolation. This approach initially predicted higher OS than the company's original approach, but predicted similar OS from year 5 to 6 onwards. In its critique of the company's response, the EAG updated its base case parametric model from the gamma to the log-logistic model. This provided better alignment with observed OS in external cohorts. The EAG added that the company's selected informative prior overestimates OS compared with pooled SPOTLIGHT and GLOW data and most external cohorts. The EAG noted that the SPOTLIGHT and GLOW trials were already mature and questioned whether adding CheckMate 649 was necessary. At the second committee meeting, the committee acknowledged that the company had explored its suggested informative prior approach. It considered the outputs of the company's informative prior analysis and noted the unexplained difference between OS in CheckMate 649 and SPOTLIGHT in particular. The committee agreed that the main benefit of using an informative prior in this instance would be if trial data was immature. SPOTLIGHT and GLOW data are reasonably mature. So, using an additional arm as the informative prior without accounting for heterogeneity in relevant treatment-effect modifiers between this arm and SPOTLIGHT or GLOW, likely increases uncertainty compared with using head-to-head data. It concluded that it preferred the EAG's approach of fitting a log-logistic parametric model to the chemotherapy arm of the pooled SPOTLIGHT and GLOW trials only.