Abstract:Background Intermediate endpoints are needed in early phase studies of men with metastatic castration-resistant prostate cancer (mCRPC) that can reliably predict success in phase 3 trials. Among men with measurable disease, objective response may provide information as to whether a treatment is likely to be successful. Methods We conducted a systematic review of systemic agents that have proceeded to phase 3 trials in men with mCRPC and examined the relationship between improvements in measurable disease respo… Show more
“…In reality, it is unlikely that this assumption will ever hold and will frequently be far from being a reasonable approximation, as there will be a degree of variability in the strength of response as a predictor and the nature of this relationship. 48 – 50 When applying a response-based modeling approach for the evaluation of HITs, it is therefore important to consider the strength of evidence supporting the surrogacy assumptions and whether the ability to generate histology-specific ICERs outweighs any associated uncertainties. Where there are substantive concerns regarding the potential for heterogeneity in survival endpoints, alternative analysis methods may be more appropriate.…”
Background The National Institute for Health and Care Excellence and a number of international health technology assessment agencies have recently undertaken appraisals of histology-independent technologies (HITs). A strong and untested assumption inherent in the submissions included identical clinical response across all tumour histologies, including new histologies unrepresented in the trial. Challenging this assumption and exploring the potential for heterogeneity has the potential to impact upon cost-effectiveness. Method Using published response data for a HIT, a Bayesian hierarchical model (BHM) was used to identify heterogeneity in response and to estimate the probability of response for each histology included in single-arm studies, which informed the submission for the HIT, larotrectinib. The probability of response for a new histology was estimated. Results were inputted into a simplified response-based economic model using hypothetical parameters. Histology-independent and histology-specific incremental cost-effectiveness ratios accounting for heterogeneity were generated. Results The results of the BHM show considerable heterogeneity in response rates across histologies. The predicted probability of response estimated by the BHM is 60.9% (95% credible interval 16.0; 91.8%), lower than the naively pooled probability of 74.5%. A mean response probability of 56.9% (0.2; 99.9%) is predicted for an unrepresented histology. Based on the economic analysis, the probability of the hypothetical HIT being cost-effective under the assumption of identical response is 78%. Allowing for heterogeneity, the probability of various approval decisions being cost-effective ranges from 93% to 11%. Conclusions Central to the challenge of reimbursement of HITs is the potential for heterogeneity. This study illustrates how heterogeneity in clinical effectiveness can result in highly variable and uncertain estimates of cost-effectiveness. This analysis can help improve understanding of the consequences of histology-independent versus histology-specific decisions.
“…In reality, it is unlikely that this assumption will ever hold and will frequently be far from being a reasonable approximation, as there will be a degree of variability in the strength of response as a predictor and the nature of this relationship. 48 – 50 When applying a response-based modeling approach for the evaluation of HITs, it is therefore important to consider the strength of evidence supporting the surrogacy assumptions and whether the ability to generate histology-specific ICERs outweighs any associated uncertainties. Where there are substantive concerns regarding the potential for heterogeneity in survival endpoints, alternative analysis methods may be more appropriate.…”
Background The National Institute for Health and Care Excellence and a number of international health technology assessment agencies have recently undertaken appraisals of histology-independent technologies (HITs). A strong and untested assumption inherent in the submissions included identical clinical response across all tumour histologies, including new histologies unrepresented in the trial. Challenging this assumption and exploring the potential for heterogeneity has the potential to impact upon cost-effectiveness. Method Using published response data for a HIT, a Bayesian hierarchical model (BHM) was used to identify heterogeneity in response and to estimate the probability of response for each histology included in single-arm studies, which informed the submission for the HIT, larotrectinib. The probability of response for a new histology was estimated. Results were inputted into a simplified response-based economic model using hypothetical parameters. Histology-independent and histology-specific incremental cost-effectiveness ratios accounting for heterogeneity were generated. Results The results of the BHM show considerable heterogeneity in response rates across histologies. The predicted probability of response estimated by the BHM is 60.9% (95% credible interval 16.0; 91.8%), lower than the naively pooled probability of 74.5%. A mean response probability of 56.9% (0.2; 99.9%) is predicted for an unrepresented histology. Based on the economic analysis, the probability of the hypothetical HIT being cost-effective under the assumption of identical response is 78%. Allowing for heterogeneity, the probability of various approval decisions being cost-effective ranges from 93% to 11%. Conclusions Central to the challenge of reimbursement of HITs is the potential for heterogeneity. This study illustrates how heterogeneity in clinical effectiveness can result in highly variable and uncertain estimates of cost-effectiveness. This analysis can help improve understanding of the consequences of histology-independent versus histology-specific decisions.
“…RECIST criteria progression is standard of care for identifying progressive disease on imaging and has a strong correlation with OS in prostate cancer (20). However, RECIST progression was less prognostic than change in either PSMA-TTV or PSA progression at study exit.…”
BACKGROUND 177 Lutetium PSMA-617 ( 177 LuPSMA-617) therapy has shown high prostate specific antigen (PSA) response rates in men with metastatic castration-resistant prostate cancer (mCRPC). However early treatment resistance is common. This LUPIN substudy aimed to determine the prognostic value of post-treatment quantitative PET for PSA progression free (PSA-PFS) and overall survival (OS) with 177 LuPSMA-617 therapy.
METHODS56 men with progressive mCRPC were enrolled in LuPIN trial and received up to 6 doses of 177 LuPSMA-617 and a radiation sensitizer (NOX66). 68 Ga-PSMA-11 and 18 F-FDG PET/CT, diagnostic CT and bone scan were performed at study entry and exit.Quantitative analysis tracked change (Δ) in total tumour volume (TTV) and standardised uptake value (SUV). Univariable and multivariable analyses were conducted to examine the association of ΔTTV (continuous and > 30%), SUVmax, PSA and radiographic progression with PSA-PFS and OS.
RESULTSAll men (37/56) who underwent both screening and post treatment molecular imaging were analyzed. 70% (26/37) had a PSA response >50%, median PSA-PFS was 8.6 months and median OS 22 months. Clinical progression had occurred at trial exit in 54% (20/37). 95% (35/37) demonstrated reduced PSMA SUVmax and 68% (25/37) reduced PSMA-TTV in response to treatment. An increase in PSMA-TTV ≥30% was
“…Can RECIST response predict success in phase 3 trials in men with metastatic castration-resistant prostate cancer? [3] A major issue in drug development in advanced prostate cancer remains the lack of surrogate intermediate end points for overall survival, which can be quite prolonged in many men. This original study examined all phase-2 and -3 trials of men with mCRPC to look at whether significant measurable disease response rates by RECIST in phase-2 trials led to positive phase-3 trials, and suggests that this may be the case for certain single agents depending on the mechanism of action of the specific therapy.…”
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