IntroductionSubgroup analyses are vital components of health technology assessments, but randomized controlled trials (RCTs) do not commonly report survival distributions for subgroups. This study developed an analytical framework to elicit unreported subgroup-specific survival curves from aggregate RCT data.MethodsAssuming exponentially distributed subgroup survival durations, we developed an optimization model that approximates the restricted mean survival time (RMST) for the overall population via the weighted average of the RMSTs of 2 subgroups in each arm. Reported hazard ratios from the forest plots between the arms were used to enforce the relationship among subgroups' hazard rates in the model. The performance of the model was tested in a real-life test set of 8 RCTs in advanced-stage gastrointestinal tumors, which also reported KM curves for overall survival (OS) for 40 subgroups as well as in 42 synthetic test cases with 168 subgroups as a benchmark. For each subgroup, predicted median survival, OS rates, and the RMSTs were compared against their actual counterparts as well as their 95% confidence intervals (CIs).ResultsPredicted median survivals and RMSTs were within the 95% CIs of the reported values in 32 (80%) and 34 (85%) of 40 subgroups in real-life test cases and in 163 (97%) and 146 (87%) of 168 subgroups in synthetic test cases, respectively. Across all cases, on average, the predicted survival curves laid within the 95% CIs of reported KM curves 71% and 97% of the time in real-life and synthetic test cases, respectively.DiscussionOur study offers a useful and scalable method for extracting subgroup-specific survival from aggregate RCT data to enable subgroup-specific indirect comparisons, and cost-utility and meta-analyses.HiglightsMost randomized controlled trials report survival curves for the overall patient population but do not provide subgroup-specific survival curves, which are crucial for cost-effectiveness analyses and meta-analyses focusing on these subgroups.This study developed an optimization modeling approach to elicit unreported subgroup-specific survival curves from aggregate trial data.The proposed modeling approach accurately predicted the reported subgroup-specific survival curves in 42 simulated test cases with 168 subgroups overall, in which each subgroup-specific survival curve was assumed to followed an exponential distribution.The performance of the proposed modeling approach was sensitive to the assumptions when it was tested using a real-life test set of 8 oncology trials, which also reported survival curves for a total of 40 subgroups.

BACKGROUND:Establishing surrogate endpoints for overall survival (OS) may expedite assessment of new therapies in esophageal cancer (EC) and gastroesophageal junction cancer (GEJC). This study aimed to evaluate disease-free survival (DFS) as a surrogate endpoint for OS. METHODS:Patients from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database aged ≥66 years with resection after primary diagnosis of stage 2 or 3 EC/GEJC between 2009 and 2017 were analyzed (N = 925; median follow-up 26.2 months). Surrogacy was assessed by evaluating individual level associations between DFS and OS using Spearman's rank correlation and the association between treatment effects by Pearson's correlation coefficient. To evaluate the association between treatment effects, patients were classified in synthetic clusters based on treatments received. Propensity score matching addressed imbalances in baseline characteristics between treatment and control groups in the clusters. Predictive performance of the surrogacy equation was assessed internally for the generated clusters via leave-one-out cross-validation and externally via predictions for 26 clinical trials of early-stage EC/GEJC. RESULTS:Patients were mostly male (84%), non-Hispanic white (89.3%), with median age 71.8 years, and cancer stages 2 (50.4%) and 3 (49.6%). Cancer types were adenocarcinoma (76.1%), squamous cell carcinoma (10.4%), and other types (13.5%). Most patients 766/925 (82.8%) received neoadjuvant therapy (680/766 chemoradiotherapy versus 86/766 chemotherapy alone) while 23.6% of the patients received adjuvant therapy. Within each treatment setting, most [705/766 (92.0%) of neoadjuvant therapy and 178/218 (81.7%) of adjuvant therapy] received multi-agent chemotherapy. The individual level correlation was 0.76 (95% confidence interval 0.70-0.80). The correlation between treatment effects was 0.96 (95% confidence interval 0.80-0.99) with a corresponding surrogate threshold effect of 0.71. Both internal (91%) and external (89%) validation of the model demonstrated high predictive accuracy. CONCLUSIONS:Correlations between DFS and OS were meaningful at both individual and treatment effect level. The derived surrogacy equation enables reliable early assessments of OS benefit from the observed DFS benefit for early-stage EC/GEJC treatments in real-world settings.

Adjuvant nivolumab is approved and reimbursed for resected patients with esophageal or gastro-esophageal junction (GEJ) cancer with incomplete response to neoadjuvant chemoradiation (nCRT) in the Netherlands since January 2022. This study investigated factors associated with uptake of adjuvant nivolumab in a nationwide population. Patients were selected from the Netherlands Cancer Registry based on the EMA indication (non-metastasized esophageal or GEJ cancer treated with nCRT plus surgery and residual pathological disease). Following the Checkmate-577 inclusion criteria, we also investigated a subpopulation using additional criteria: R0 resection and WHO performance status 0-1. Treatment with nivolumab is presented according to time of surgery. The association of not administering nivolumab with patient, disease and treatment characteristics was assessed with multivariable logistic regression. Of 275 eligible patients in the EMA-indicated population, 177 (64%) were treated with adjuvant nivolumab. Uptake increased from 51% in November-December 2021 to 72%, 68%, and 66% in Q1, Q2 and Q3 of 2022, respectively. According to the Checkmate-577 criteria, 215 patients were eligible, of whom 147 (68%) were treated with nivolumab, with a similar pattern over time (49%, 78%, 67% and 76%, respectively). In the EMA-indicated population, nivolumab was administered less often to patients with ypN0-1 nodal status, irradical resection, post-operative grade 3-4 complications and patients undergoing a gastrectomy (Table). Table: 1575PFactors associated with nivolumab treatmentVariableNUnivariable proportion treated with adjuvant nivolumabMultivariable odds ratios on not starting with adjuvant nivolumab (95% confidence interval)P-valueAge (continuous)275Not applicable1.02 (0.99 – 1.05)0.28ypN- ypN013056%3.54 (1.57 – 7.98)<0.01- ypN19266%2.43 (1.04 – 5.69)0.04- ypN2-35379%RefType of surgery- Esophagectomy26765%Ref- Total gastrectomy812%12.13 (1.41 – 105.6)0.02Surgical radicality- R022267%Ref- R1-24949%2.91 (1.45 – 5.87)<0.01- Unknown475%0.81 (0.08 – 8.83)0.86Post-operative grade 3-4 Clavien-Dindo complications- No grade 3-4 complication21768%Ref- Grade 3-4 complication5850%2.11 (1.13 – 3.96)<0.01 Open table in a new tab Treatment with adjuvant nivolumab has been implemented in the Netherlands, reaching a quarterly maximum of 72-78% of theoretically eligible patients. Small differences in uptake were found between eligible populations based on EMA indicated and Checkmate-577 criteria. Specific disease and treatment characteristics were associated with administration of nivolumab.

To evaluate RFS as a surrogate endpoint for OS in early-stage HCC by assessing treatment-level correlations using published literature.

In the phase 3 clinical trial, CheckMate 577, patients with resected EC/GEJC treated with nivolumab had statistically significant and clinically meaningful improvement, versus placebo, in the primary endpoint, disease-free survival (DFS). Overall survival (OS) data is currently not available. The objective of this study was to evaluate approaches for estimating post-recurrence survival (PRS) to populate a cost-effectiveness model (CEM) for CM577 and assess sensitivity. To determine the ICUR over 30-years in Canada, the CEM adopted a three-health state (3-HS) Markov model (pre-recurrence, post-recurrence, death) allowing flexibility to include external data sources to estimate PRS. Two PRS data sources were explored: (i) adjuvant patients with EC/GEJC from the Netherlands Comprehensive Cancer Organization (IKNL) registry matched to the CM 577 population and (ii) first-line (1L) patients with advanced EC/GEJC OS pooled from clinical trials CM 649 and KEYNOTE- 590. The IKNL registry data were also analyzed by type of recurrence (locoregional and distant) to explore model sensitivity to a 3-HS approach (pooling type of recurrence) versus a 4-HS approach with patients separated by type of recurrence. The CEM assumed the same PRS for each treatment arm, based on clinical opinion. Using adjuvant IKNL registry PRS data in the 3-HS model, the ICUR of nivolumab versus surveillance was $42,733/QALY gained. Using IKNL data in the 4-HS model, the ICUR was $42,920/QALY gained. Using 1L advanced EC/GEJC trial data in the 3-HS model, the ICER was $45,961/QALY gained. The CEM for nivolumab in the adjuvant setting for patients with resected EC/GEJC in Canada is not sensitive to the data source for PRS or analysis by type of recurrence (3-HS or 4-HS) in the absence of OS data. Introducing additional complexity to the analysis by type of recurrence did not produce varying results in the adjuvant EC/GEJC setting, and therefore 3 HS model is preferred.

Esophageal cancer (EC) is the third most common digestive cancer in France with an incidence of 5450 new cases in 2018. All stages combined the prognosis remains poor with 5-year survival rates around 14%. In non-metastatic patients, the benefits of adding perioperative chemotherapy (CT) or neoadjuvant chemoradiotherapy (NACRT) to surgery have been demonstrated and are currently recommended. Immune checkpoint inhibitors (ICI) have showed promising results. The aim of the study was to provide real-world treatment outcomes before arrival of ICI in the therapeutic arsenal.

Esophageal cancer is the seventh most common cancer and sixth leading cause of cancer death, worldwide, with approximately 600,000 new cases and over 540,000 deaths in 2020. Squamous-cell carcinoma accounts for approximately 60% of cases in Europe. The study aim was to describe real-world treatment and outcomes of French patients presenting with UnResectable Advanced, or Metastatic Esophageal Squamous-Cell Carcinoma (URAM-ESCC) from 2014 to 2019 before approval of immune-checkpoint inhibitors (ICI).

The primary objective of this study was to evaluate the incremental cost-utility ratio (ICUR) for the adjuvant treatment of patients with resected EC/GEJC tumour in Canada. This analysis is based on outcomes of the phase 3 clinical trial, CheckMate 577, in which patients with resected EC/GEJC had statistically significant and clinically meaningful improvement in its primary endpoint, disease-free survival (DFS), versus placebo with an acceptable safety profile following neoadjuvant chemoradiotherapy. A three-health state Markov model (pre-recurrence, post-recurrence, and death) was developed to determine the ICUR of nivolumab vs. surveillance over 30 years. CM577 DFS data estimated the transition from pre-recurrence to post-recurrence. As overall survival data were not available, the transition from post-recurrence to death was estimated with IKNL registry data matched to the CM577 population, independent of treatment. The transition from pre-recurrence to death was estimated by combining CM577 and general population mortality data, independent of treatment. Utility data were from CM577 and cost data from clinical input and published literature, costs were based on a maximum nivolumab treatment duration of 1-year, per CM577. Nivolumab and surveillance patients in pre-recurrence from 3-years onwards were assumed to remain in a disease-free health state based on CM577 data. In the probabilistic-approach reference case, the ICUR of nivolumab versus surveillance was $42,733/QALY gained, at list price. Nivolumab was associated with incremental cost of $71,474 and incremental QALY gain of 1.67. Nivolumab had a 92% probability of being cost-effective at a willingness to pay (WTP) threshold of $100,000/QALY. The ICUR remained below this threshold for all scenarios, with results ranging from $32,854/QALY to $92,681/QALY, when TTR instead of DFS was used for pre-recurrence to post-recurrence transition and time horizon reduced to 10 years, respectively. Nivolumab is a cost-effective option in the adjuvant setting for patients with resected EC or GEJC in Canada.

Validation of intermediate endpoints such as disease-free survival (DFS) and progression-free survival (PFS) as surrogate predictors for overall survival (OS) in randomized controlled trials (RCTs) requires establishing their association at the individual-level. In the absence of individual-level patient data (IPD), this study developed an analytical framework to estimate this association between DFS/PFS and OS using reported Kaplan-Meier (KM) curves from the RCTs and demonstrated its predictive performance in adjuvant and metastatic gastric cancer (GC) treatment settings.

Survival heterogeneity across subgroups play a critical role in the evaluation of reimbursement dossiers by health technology assessment agencies. This study offers an optimization-based approach to elicit unreported subgroup-specific Kaplan-Meier (KM) curves using aggregate level data from RCTs.

RCTs often report only relative efficacy measures for subgroups disabling a robust comparison of their long-term survival for subsequent cost-effectiveness analyses. We devised an analytical framework to elicit unreported subgroup specific survival from the aggregate RCT data using lifetime mean survival (LTMS) as an objective. Reconstructed Kaplan-Meier (KM) curves for overall survival (OS) were extrapolated over lifetime using parametric survival models and adjusted with background mortality rates to estimate LTMS in both arms of RCT. By expressing the LTMS in each arm as a weighted average of the mean survival of two select subgroups and assuming exponentially distributed subgroup survival times, hazard rates of the distributions were derived as a closed form solution to two linear equations. Model performance was tested in a case study of 18 distinct RCTs from advanced stage gastrointestinal tumors reporting KM-curves for validation in 96 subgroups in total. For each subgroup predicted median OS (mOS) was compared to 95% CI of the reported mOS. Predictive accuracy of the method was compared to an alternative approach using an objective relying on restricted mean survival time (RMST) limited by the trial follow-up. LTMS-based approach showed median alignment in 23 subgroups, which was 27 subgroups less than the alignment achieved by RMST-based approach. RMST-based approach had median alignment in 32 subgroups where LTMS-based approach showed none. In 4 RCTs where RMST-based approach showed median alignment in all subgroups, LTMS-based approach showed no alignment in any subgroups. When RMST-based approach allowed subgroup-specific survival times to follow Weibull or loglogistic distribution, median alignment improved by 54 subgroups over LTMS-based approach. Considering splines and dependent models between the arms for survival extrapolations did not improve the performance of LTMS-based approach. Eliciting subgroup survival using RMST than LTMS can be more accurate and freer of the uncertainty introduced by long-term survival extrapolations.

This study devises a systematic approach that can utilize aggregate level survival and comparative effectiveness data published from randomized controlled trials (RCT) to assist subgroup-specific health economic and meta-analyses. We developed a soft-constrained optimization model, which approximates the restricted mean survival time (RMST) for the overall population in each arm via weighted sum of the RMSTs of two subgroups of interest. Survivals of both subgroups in each arm were assumed to follow Weibull or log-logistic distribution. The constraint ensured that cumulative hazards between the arms were proportional for each subgroup at a sufficiently long pre-specified time point. Estimated subgroup-specific survival functions for the control arm were direct outputs of the model and were shifted by applying the reported hazard ratios from the forest plots to generate their counterparts for the intervention arm assuming proportional hazards between the arms. For validation, we tested our approach in a case study consisting of 10 distinct RCTs with reported subgroup-specific Kaplan-Meier (KM) curves from advanced stage gastrointestinal tumors. Across all 48 subgroups, on average, loglogistic model performed equally or better than Weibull model in performance criteria comparing overall survival (OS) rates, median OS and RMSTs. Predicted survival curves laid within the 95% confidence intervals (CIs) of reported KM-curves in 75% and 81% of the time for Weibull and loglogistic models, respectively. Predicted median survivals were within the 95% CIs of the reported medians in 34 and 40 subgroups for Weibull and loglogistic models, respectively. Average relative gap between the predicted and reported RMSTs was 10% in both models. Predicted RMSTs were within the 95% CI of reported RMSTs in 34 and 37 subgroups for Weibull and loglogistic models, respectively. Our elicitation approach is effective and demonstrably reliable in deriving unreported subgroup survival with flexible time-varying hazard functions.

The number needed to treat (NNT) analysis offers a simple approach to estimate the relative benefit of a new therapy by estimating the number of patients needed to be treated to prevent an additional outcome. CheckMate 577 was a global randomized, placebo (i.e. surveillance) controlled phase 3 trial of patients with EC/GEJC who previously received chemoradiotherapy followed by resection. Patients receiving adjuvant nivolumab had a statistically significant and clinically meaningful improvement in the primary endpoint, disease-free survival (DFS), versus surveillance.

Switzerland recently approved and reimbursed nivolumab as the first adjuvant treatment for patients with resected esophageal cancer (EC) or gastroesophageal junction cancer (GEJC). A phase 3 randomised controlled trial (CM577) comparing nivolumab with placebo in patients with resected EC or GEJC found that nivolumab was associated with 31% lower risk of recurrence or death and double the median disease-free survival compared with placebo. We evaluated the cost-utility of nivolumab compared with placebo from a Swiss compulsory health insurance system perspective.

Treatment patterns for surgically resected esophageal cancer (EC) and gastroesophageal junction cancer (GEJC) vary across Europe. This study describes real-world treatment patterns and outcomes for patients receiving surgery for stage II or III EC or GEJC. In this retrospective, non-interventional chart review, physicians in Europe (UK, France, Italy, Germany, Spain) were asked to provide clinical and treatment data about their EC and GEJC patients. Patients included were ≥18 years old and underwent surgical resection (index) of Stage II or III cancer between October 2017 and October 2018. Data were collected from medical records until death, loss to follow-up, or end of data collection (June 2020). 252 physicians reported data for 734 patients who received surgery for Stage II or III esophageal squamous cell carcinoma (ESCC) (21%), esophageal adenocarcinoma (EAC) (40%), or GEJC (39%). Patients had a mean age of 62.5 years, 80.4% were male, and 84.9% had an ECOG score of 0 or 1 at the time of diagnosis. Over two-thirds of patients received R0 resection (70.5%). For patients who received neoadjuvant therapy, 69.9% did not experience complete pathological response to treatment. The median (IQR) follow-up was 26.0 (18.0-31.0) months. Among the 734 patients, 66.3% (n=487) received neoadjuvant therapy, 31.5% (n=231) of which was neoadjuvant chemoradiotherapy (CRT), 28.3% (n=208) of which was neoadjuvant chemotherapy and 6.5% (n=48) of which was radiation alone. The most common neoadjuvant CRT regimens were cisplatin + 5-FU (26.4%) and carboplatin + paclitaxel (26.4%). The most common neoadjuvant chemotherapy regimens used were docetaxel + oxaliplatin + leucovorin + 5-FU (FLOT; 26%) and cisplatin + 5-FU (15.9). Cisplatin + 5-FU was more common in ESCC patients, while the FLOT regimen was more commonly used in GEJC and EAC patients. Following surgery, a majority of patients (54.1%) did not receive adjuvant therapy. For patients who received neoadjuvant CRT prior to surgery, less than 30 patients in each country received adjuvant treatment. For patients who received neoadjuvant chemotherapy prior to surgery, 50% also received chemotherapy after surgery. Of all included patients, 22.2% experienced locoregional or metastatic recurrence and 6.1% of patients died during the data collection period. Among those who recurred, the median time to recurrence was 6.0 (0.0-26.0) months. This real-world study showed that a majority of stage II/III EC/GEJC patients received neoadjuvant treatment prior to surgery, however, 69.9% still had residual disease (non-pathological complete response). After surgery, the majority of patients did not receive adjuvant treatment which is in line with clinical guidelines, and disease recurrence was common. These observations indicate a high unmet need in this patient population for more effective treatment options in the adjuvant setting.

from CheckMate-577 (CM-577) Trial In the global, double-blind, randomized Phase 3 CM-577 trial involving patients with resected EC/GEJC previously treated with neoadjuvant chemoradiotherapy, adjuvant nivolumab therapy was associated with improvement in disease-free survival, similar quality of life relative to placebo, and was well tolerated. This study examined the HCRU of patients during adjuvant treatment with nivolumab versus placebo in CM-577. Data on hospital admissions and non-protocol-specified visits (NPSVs)—the latter defined as hospital outpatient, emergency room, physician office, home healthcare, or other visits—were collected from all 794 randomized CM-577 participants during treatment (patients treated for one year or until disease progression). Frequency and duration of hospital admissions and NPSVs were summarized and exposure-adjusted analysis of hospitalizations, including calculation of exposure-adjusted incidence rate ratio (IRRs) for reduction of incidence with nivolumab versus placebo, was completed by modelling events using negative binomial regression accounting for treatment duration as an offset variable. During treatment, 25% of patients on nivolumab and 28% of patients on placebo experienced at least one hospitalization, with 18% (nivolumab) and 22% (placebo) experiencing a single hospitalization. Median length of hospitalization was 8 and 6 days for nivolumab and placebo, respectively. Average treatment exposure was similar in each arm; adjusting for treatment exposure, the incidence of hospital admission was similar for patients treated with nivolumab versus placebo (0.78 versus 0.69 admissions/patient/year; IRR=1.12 [95% CI 0.78, 1.62]). Frequency of NPSV was similar between treatment arms (nivolumab 33%; placebo 32%), with <20% of patients in each arm requiring >1 NPSV. The most common types of NPSVs in both arms were hospital outpatient and physician office visits. In CM-577, patients with EC/GEJC receiving adjuvant nivolumab treatment did not have significantly higher HCRU than patients receiving placebo. These findings further support clinical data to demonstrate treatment benefit and tolerability for adjuvant nivolumab in patients with resected EC/GEJC.

GBM patients experience debilitating neurological and physical symptoms often requiring caregiver support. This study explored burden among caregivers of GBM patients. Real-world data were drawn from the GBM Disease-Specific ProgrammeTM – a cross-sectional study administered to physicians and caregivers between May-July 2016 (EU5) and March-October 2019 (US). Caregivers completed a caregiver self-completion form (CSC) that captured demographics, care provided and caregiver burden (Zarit Burden Interview [ZBI]). ZBI scores range between 0-88; higher scores indicating greater burden. The corresponding burden for a score <20 is 'low', 20-40 is 'mild-moderate', and >40 is 'high'. CSCs were matched with corresponding patient record forms. Summary statistics were reported and descriptively analysed. 304 CSCs were completed. Mean (SD) age of caregivers was 55.7 (12.08), 31% were male, 70% were a partner/spouse and 82% resided with the patient. GBM patients with caregivers were mean (SD) age of 62.4 (12.40) years and 64% were male. Mean (SD) time since GBM diagnosis was 8.1 (6.6) months. Most patients had an ECOG score of 2 (37%) at time of data collection. 51% were on first line therapy, 55% had received both surgery and radiotherapy, and 45% had comorbidities. Mean (SD) overall ZBI score was 32.2 (15.76), 23% of caregivers had a ZBI score of <20 (low burden), 45% of 20–40 (mild-moderate burden) and 32% of >40 (high burden). Patients whose caregivers had high burden had a shorter mean time since diagnosis (230.1 days) compared with patients whose caregivers experienced mild-moderate or low burden (234.6 days and 305.9 days respectively). Among patients whose caregivers experienced high burden; 53% had comorbidities, 65% had an ECOG score ≥2 and 45% had received both surgery and radiotherapy. Most caregivers experience substantial burden. Consideration should be given to support GBM patients and their caregivers, particularly when patients have comorbidities.

Real-world first line (1L) treatment patterns and outcomes in patients with R/M SCCHN are not fully known. A retrospective chart review was conducted in France, Germany and the UK to characterize patients, treatment and outcomes. Nineteen oncologists contributed data on 109 patients age ≥18 years diagnosed with R/M SCCHN between 01-Jan-2014 and 31-Dec-2016. Patients were followed through May 2020 or until death. Clinical trial participants were excluded. Demographics and treatments were analyzed descriptively. Overall survival (OS) and real-world progression-free survival (rwPFS) were quantified using Kaplan-Meier analysis, censoring for chart abstraction date in surviving non-progressing patients. Patients were a mean (SD) age of 61 (10) years and 63% were known current or former tobacco users at R/M SCCHN diagnosis. At 1L treatment initiation for R/M SCCHN, 62% were platinum naïve/de novo metastatic, 15% were deemed platinum sensitive, and the remainder were platinum refractory or unknown. EXTREME (Cetuximab+Cisplatin+5-Fluorouracil) was administered to 29%, 28% received platinum combination therapy with or without a taxane, 27% received platinum monotherapy, and 9% received other cetuximab-based therapy and the remainder receiving “other”. For all 1L R/M SCCHN patients, median OS (95%CI) was 10.0 (7.1, 12.8) months, and rwPFS was 5.9 (4.1, 7.7) months. Landmark 6, 12, 24- and 36-month OS was 69.4%, 45.5%, 24.2% and 15.4%, respectively. Cetuximab and platinum-based regimens were the mainstay of therapy in 1L R/M SCCHN, with a grim prognosis. This study highlights the need for more effective treatments in a patient population with a significant level of unmet need.