Pcn451 Modeling the Survival Benefit of Immuno-Oncologic Therapy: A Review of Methods Used in Nice Single Technology Appraisals

Kroep, Sonja; Kiff, Christopher; Kraan, C.W.; Bianco, M.A.; Johannesen, Kasper; Kurt, Murat; Malcolm, Bill; Wu, Elise; Fenwick, E. Hurry; Klijn, S.; Borrill, J.

doi:10.1016/j.jval.2019.09.643

Cited by 4 publications

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“…This study estimated and compared the following 6 survival modeling techniques that have been used to estimate the long-term survival of patients with cancer treated with immune checkpoint inhibitors: standard parametric, piecewise, cubic spline, mixture cure, parametric mixture, and landmark response models ( Figure 1 ). 7 , 8 , 10 , 12 Standard parametric models are more widely used and established for health technology assessments than the other methods and are typically considered the starting point for survival extrapolation in the absence of a complex hazard. Because standard hazard functions are less complex, they are generally easier to interpret and more parsimonious.…”

Section: Methodsmentioning

confidence: 99%

“… 1 , 6 Piecewise and cubic spline models allow for additional flexibility mechanistically in fitting the hazard function. 5 – 8 , 12 Mixture cure, parametric mixture, and landmark response models provide flexibility by explicitly assuming survival heterogeneity. 5 – 8 , 12 In fact, parametric mixture models subsume standard parametric and mixture cure models as special cases.…”

Section: Methodsmentioning

confidence: 99%

“… 5 – 8 , 12 Mixture cure, parametric mixture, and landmark response models provide flexibility by explicitly assuming survival heterogeneity. 5 – 8 , 12 In fact, parametric mixture models subsume standard parametric and mixture cure models as special cases. Detailed descriptions of the parameterization for each modeling approach are provided in the Supplemental Material .…”

Section: Methodsmentioning

confidence: 99%

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Heterogeneity in Survival with Immune Checkpoint Inhibitors and Its Implications for Survival Extrapolations: A Case Study in Advanced Melanoma

Paly

Kurt

Zhang

et al. 2022

MDM Policy & Practice

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Background Survival heterogeneity and limited trial follow-up present challenges for estimating lifetime benefits of oncology therapies. This study used CheckMate 067 (NCT01844505) extended follow-up data to assess the predictive accuracy of standard parametric and flexible models in estimating the long-term overall survival benefit of nivolumab plus ipilimumab (an immune checkpoint inhibitor combination) in advanced melanoma. Methods Six sets of survival models (standard parametric, piecewise, cubic spline, mixture cure, parametric mixture, and landmark response models) were independently fitted to overall survival data for treatments in CheckMate 067 (nivolumab plus ipilimumab, nivolumab, and ipilimumab) using successive data cuts (28, 40, 52, and 60 mo). Standard parametric models allow survival extrapolation in the absence of a complex hazard. Piecewise and cubic spline models allow additional flexibility in fitting the hazard function. Mixture cure, parametric mixture, and landmark response models provide flexibility by explicitly incorporating survival heterogeneity. Sixty-month follow-up data, external ipilimumab data, and clinical expert opinion were used to evaluate model estimation accuracy. Lifetime survival projections were compared using a 5% discount rate. Results Standard parametric, piecewise, and cubic spline models underestimated overall survival at 60 mo for the 28-mo data cut. Compared with other models, mixture cure, parametric mixture, and landmark response models provided more accurate long-term overall survival estimates versus external data, higher mean survival benefit over 20 y for the 28-mo data cut, and more consistent 20-y mean overall survival estimates across data cuts. Conclusion This case study demonstrates that survival models explicitly incorporating survival heterogeneity showed greater accuracy for early data cuts than standard parametric models did, consistent with similar immune checkpoint inhibitor survival validation studies in advanced melanoma. Research is required to assess generalizability to other tumors and disease stages. Highlights Given that short clinical trial follow-up periods and survival heterogeneity introduce uncertainty in the health technology assessment of oncology therapies, this study evaluated the suitability of conventional parametric survival modeling approaches as compared with more flexible models in the context of immune checkpoint inhibitors that have the potential to provide lasting survival beneﬁts. This study used extended follow-up data from the phase III CheckMate 067 trial (NCT01844505) to assess the predictive accuracy of standard parametric models in comparison with more flexible methods for estimating the long-term survival benefit of the immune checkpoint inhibitor combination of nivolumab plus ipilimumab in advanced melanoma. Mixture cure, parametric mixture, and landmark response models provided more accurate estimates of long-term overall survival versus external data than other models tested. In this case study with immune checkpoint inhibitor therapies in advanced melanoma, extrapolation models that explicitly incorporate differences in cancer survival between observed or latent subgroups showed greater accuracy with both early and later data cuts than other approaches did.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Heterogeneity in Survival with Immune Checkpoint Inhibitors and Its Implications for Survival Extrapolations: A Case Study in Advanced Melanoma

Paly

Kurt

Zhang

et al. 2022

MDM Policy & Practice

View full text Add to dashboard Cite

show abstract

“…Only one CE assessment report (see study (10)) used external data to directly inform the extrapolation model. This raises questions on the reasons why other modeling approaches (59) were not considered. One possible explanation is that the acceptability of these new approaches for HTAs undertaken by the French health authorities is currently unknown, as their recommendations on extrapolation of survival data are limited (14).…”

Section: Discussionmentioning

confidence: 99%

A Review of Overall Survival Extrapolations of Immune-Checkpoint Inhibitors Used in Health Technology Assessments by the French Health Authorities

Grumberg

Roze²,

Chevalier³

et al. 2022

Int J Technol Assess Health Care

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Objectives Extrapolation is often required to inform cost-effectiveness (CE) evaluations of immune-checkpoint inhibitors (ICIs) since survival data from pivotal clinical trials are seldom complete. The objectives of this study were to evaluate the accuracy of estimates of long-term overall survival (OS) predicted in French CE assessment reports of ICIs, and to identify models presenting the best fit to the observed long-term survival data. Methods A systematic review of French assessment reports of ICIs in the metastatic setting since inception until May 2020 was performed. A targeted literature review was conducted to collect associated extended follow-up of randomized controlled trials (RCTs) used in the CE assessment reports. Difference between projected and observed OS was calculated. A range of standard parametric and spline-based models were applied to the extended follow-up data from the RCT to determine the best-fitting survival models. Results Of the 121 CE assessment reports published, 11 reports met the inclusion criteria. OS was underestimated in 73 percent of the CE assessment reports. The mean relative difference between each source was −13 percent (median: −15 percent; IQR: −0.4 to 26 percent). Models providing the best fit were those that could reflect nonmonotonic hazards. Conclusions Based on the available data at the time of submission, longer-term survival of ICIs was not fully captured by the extrapolation models used in CE assessments. Standard and flexible parametric models which can capture nonmonotonic hazard functions provided the best fit to the extended follow-up data. However, these models may still have performed poorly if fitted to survival data available at the time of submission to the French National Authority for Health.

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“…Consistency in statistical analytics is a critical consideration since different extrapolation techniques yield different model results and different product valuations, which could have downstream impacts on payer formulary decisions and patient access to care. While some publications have reviewed and compared survival extrapolation techniques for immunooncologic therapies [13,[21][22][23][24][25][26][27][28][29][30][31], none have evaluated survival extrapolation trends across the full range of publications (i.e., peer-reviewed or conference proceedings) nor global HTA agencies specifically for CAR-T therapies. To this end, the goal of this research was to conduct a systematic literature review of analyses projecting the survival benefits of CAR-T therapies over time, in an effort to ascertain research trends in survival extrapolation techniques used and the rationale for selecting advanced techniques.…”

Section: Introductionmentioning

confidence: 99%

Applying State-of-the-Art Survival Extrapolation Techniques to the Evaluation of CAR-T Therapies: Evidence from a Systematic Literature Review

et al. 2021

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Introduction: Traditional statistical techniques for extrapolating short-term survival data for anticancer therapies assume the same mortality rate for noncured and ''cured'' patients, which is appropriate for projecting survival of non-curative therapies but may lead to an underestimation of the treatment effectiveness for potentially curative therapies. Our objective was to ascertain research trends in survival extrapolation techniques used to project the survival benefits of chimeric antigen receptor T cell (CAR-T) therapies. Methods: A global systematic literature search produced a review of survival analyses of CAR-T therapies, published between January 1, 2015 and December 14, 2020, based on publications sourced from MEDLINE, scientific conferences, and health technology assessment agencies. Trends in survival extrapolation techniques used, and the rationale for selecting advanced techniques, are discussed.

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Pcn451 Modeling the Survival Benefit of Immuno-Oncologic Therapy: A Review of Methods Used in Nice Single Technology Appraisals

Cited by 4 publications

References 0 publications

Heterogeneity in Survival with Immune Checkpoint Inhibitors and Its Implications for Survival Extrapolations: A Case Study in Advanced Melanoma

Heterogeneity in Survival with Immune Checkpoint Inhibitors and Its Implications for Survival Extrapolations: A Case Study in Advanced Melanoma

A Review of Overall Survival Extrapolations of Immune-Checkpoint Inhibitors Used in Health Technology Assessments by the French Health Authorities

Applying State-of-the-Art Survival Extrapolation Techniques to the Evaluation of CAR-T Therapies: Evidence from a Systematic Literature Review

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