Over the past decade, costs of novel oncology drugs have increased, while clinical benefits of these medications have not experienced a proportional positive change. The incremental anticancer drug costs have increased at a much greater rate than monthly prices, indicating that the increase in anticancer drug costs may be higher than commonly reported.

BackgroundIn Ontario, FOLFIRINOX (FFX) and gemcitabine + nab‐paclitaxel (GnP) have been publicly funded for first‐line unresectable locally advanced pancreatic cancer (uLAPC) or metastatic pancreatic cancer (mPC) since April 2015. We examined the real‐world effectiveness and safety of FFX vs GnP for advanced pancreatic cancer, and in uLAPC and mPC.MethodsPatients receiving first‐line FFX or GnP from April 2015 to March 2017 were identified in the New Drug Funding Program database. Baseline characteristics and outcomes were obtained through the Ontario Cancer Registry and other population‐based databases. Overall survival (OS) was assessed using Kaplan‐Meier and weighted Cox proportional hazard models, weighted by the inverse propensity score adjusting for baseline characteristics. Weighted odds ratio (OR) for hospitalization and emergency department visits (EDV) were estimated from weighted logistic regression models.ResultsFor 1130 patients (632 FFX, 498 GnP), crude median OS was 9.6 and 6.1 months for FFX and GnP, respectively. Weighted OS was improved for FFX vs GnP (HR = 0.77, 0.70‐0.85). Less frequent EDV and hospitalization were observed in FFX (EDV: 67.8%; Hospitalization: 49.2%) than GnP (EDV: 77.7%; Hospitalization: 59.3%). More frequent febrile neutropenia‐related hospitalization was observed in FFX (5.8%) than GnP (3.3%). Risk of EDV and hospitalization were significantly lower for FFX vs GnP (EDV: OR = 0.68, P = .0001; Hospitalization: OR = 0.76, P = .002), whereas the risk of febrile neutropenia‐related hospitalization was significantly higher (OR = 2.12, P = .001). Outcomes for uLAPC and mPC were similar.ConclusionIn the real world, FFX had longer OS, less frequent all‐cause EDV and all‐cause hospitalization, but more febrile neutropenia‐related hospitalization compared to GnP.

Background: The open-label, phase III KEYNOTE-361 study compares efficacy and safety of 1L P + C vs C for advanced UC (NCT02853305).

Purpose Whether the ASCO Value Framework and the European Society for Medical Oncology (ESMO) Magnitude of Clinical Benefit Scale (MCBS) measure similar constructs of clinical benefit is unclear. It is also unclear how they relate to quality-adjusted life-years (QALYs) and funding recommendations in the United Kingdom and Canada. Methods Randomized clinical trials of oncology drug approvals by the US Food and Drug Administration, European Medicines Agency, and Health Canada between 2006 and August 2015 were identified and scored using the ASCO version 1 (v1) framework, ASCO version 2 (v2) framework, and ESMO-MCBS by at least two independent reviewers. Spearman correlation coefficients were calculated to assess construct (between frameworks) and criterion validity (against QALYs from the National Institute for Health and Care Excellence [NICE] and the pan-Canadian Oncology Drug Review [pCODR]). Associations between scores and NICE/pCODR recommendations were examined. Inter-rater reliability was assessed using intraclass correlation coefficients. Results From 109 included randomized clinical trials, 108 ASCOv1, 111 ASCOv2, and 83 ESMO scores were determined. Correlation coefficients for ASCOv1 versus ESMO, ASCOv2 versus ESMO, and ASCOv1 versus ASCOv2 were 0.36 (95% CI, 0.15 to 0.54), 0.17 (95% CI, -0.06 to 0.37), and 0.50 (95% CI, 0.35 to 0.63), respectively. Compared with NICE QALYs, correlation coefficients were 0.45 (ASCOv1), 0.53 (ASCOv2), and 0.46 (ESMO); with pCODR QALYs, coefficients were 0.19 (ASCOv1), 0.20 (ASCOv2), and 0.36 (ESMO). None of the frameworks were significantly associated with NICE/pCODR recommendations. Inter-rater reliability was good for all frameworks. Conclusion The weak-to-moderate correlations of the ASCO frameworks with the ESMO-MCBS, as well as their correlations with QALYs and with NICE/pCODR funding recommendations, suggest different constructs of clinical benefit measured. Construct convergent validity with the ESMO-MCBS did not increase with the updated ASCO framework.

PurposeA conceptual framework for collaboratively based integrated health and social care (IHSC) integration is proposed to aid in understanding how to accomplish IHSC.Design/methodology/approachThis model is based on extant literature of successfully IHSC initiatives.FindingsThe model aims to identify enabling integration factors that support collaborative integration efforts between healthcare and social services organizations. These factors include shared goals and vision, culture, leadership, team-based care, information sharing and communications, performance measurement and accountability agreements, and dedicated resources and financing. It also identifies factors that act as external influencers that can support or hinder integration efforts among collaborating organizations. These factors are geographic setting, funding models, governance structures, and public policies. These factors are intended to ensure that a realist lens is applied when trying to understand and explain IHSC.Originality/valueThis model is intended to provide a framework to support research, policy and implementation efforts.

Objective Various statistical methods have been developed to estimate hazard ratios (HRs) from published Kaplan‐Meier (KM) curves for the purpose of performing meta‐analyses. The objective of this study was to determine the reliability, accuracy, and precision of four commonly used methods by Guyot, Williamson, Parmar, and Hoyle and Henley. Design Pivotal randomized controlled trials (RCTs) in oncology were identified from the pan‐Canadian Oncology Drug Review (pCODR) database (primary analysis) and the Food and Drug Administration's (FDA) drug approvals page (secondary analysis) between January 2012 and May 2016. Two reviewers independently reconstructed HRs using each method on KM curves extracted from each trial and compared them with reported HRs (gold standard). Bland‐Altman plots and summary statistics were calculated to assess accuracy and precision of these methods. Interrater reliability was assessed using intraclass correlation coefficient (ICC). These four methods were also applied to KM curves of different structures (ie, flat versus steep curves). Results A total of 118 KM curves (55 RCTs) and 77 KM curves (46 RCTs) were extracted from pCODR and FDA, respectively. In the primary analysis, the Guyot method was the most accurate with the lowest mean error (0.0094; 95% CI, −0.0012‐0.020). All four methods had excellent interrater reliability. The Guyot method showed the smallest bias and greatest precision on the Bland‐Altman plots. The Guyot method was consistently superior in both the secondary and all sensitivity analyses. Conclusion In the absence of reported HRs, we recommend that researchers consider the Guyot method to reconstruct HRs from KM curves when performing aggregate data meta‐analyses.

ASCO) and the European Society for Medical Oncology (ESMO) have independently published value frameworks. To date, whether the clinical benefit scoring algorithms from these framework were intended to measure absolute or relative survival benefit remains unclear.OBJECTIVE To empirically examine the measurement characteristics of these frameworks by comparing their survival efficacy components (ASCO clinical benefit score [CBS] and ESMO preliminary magnitude of clinical benefit grade [PMCBG]) with established measures of absolute (median survival difference and restricted mean survival time [RMST] difference) and relative (hazard ratios [HRs]) survival benefit. DATA SOURCESThe US Food and Drug Administration (FDA)'s Hematology and Oncology Approvals and Safety Notifications database was retrospectively reviewed to identify phase 3 randomized controlled trials (RCTs) cited for clinical efficacy evidence in oncology drug approvals from January 1, 2006, through December 31, 2017.STUDY SELECTION Two reviewers searched the database for initial trials cited for approval. Phase 3 trials with overall survival, progression-free survival, and/or time to progression as their primary or coprimary end points were included. Notifications for noncancer indications or presenting label changes and trials that did not report HRs for the required end points and/or did not publish survival curves with number-at-risk data were excluded. Of 269 notifications initially identified, 107 met the selection criteria.DATA EXTRACTION AND SYNTHESIS Sensitivity analyses were conducted by calculating the scores using (1) the framework-defined end point, including tail-of-curve bonus points (ASCO) or long-term plateau adjustments (ESMO) (framework-defined end point plus tail-of-curve bonus), (2) overall survival data only, and (3) progression-free survival data only. For primary and xsensitivity analyses, Spearman correlation coefficients were calculated to examine the xrelationships between (1) ASCO-CBS or ESMO-PMCBG and RMST difference, (2) ASCO-CBS or ESMO-PMCBG and median survival difference, and (3) ASCO-CBS or ESMO-PMCBG and HR. Data were analyzed from January 7 through April 30, 2018. MAIN OUTCOMES AND MEASURESIn the primary analysis, ASCO-CBSs and ESMO-PMCBGs were calculated for the included trials using the framework-defined end point. RESULTSCompared with measures of absolute survival benefit, ESMO-PMCBGs showed low to moderate correlations with RMST difference (ρ = 0.44) and moderate to high correlations with median survival difference (ρ = 0.64). ASCO-CBSs showed low to moderate correlations with both measures of absolute benefit (ρ = 0.43 for RMST difference; ρ = 0.44 for median survival). Compared with a relative measure of survival (HRs), ESMO-PMCBGs showed a low correlation (ρ = 0.47) and ASCO-CBSs showed a higher correlation (ρ = 0.76). CONCLUSIONS AND RELEVANCENeither framework consistently performed as an absolute measure of survival benefit. The incorporation of a direct measure of absolute clinical benefit, such as RMST differ...

BackgroundWhether patients with excellent and reduced performance status (PS) derive different net clinical benefit from novel anticancer systemic therapies on clinical trials is unclear.Materials and methodsA systematic review was conducted of randomised controlled trials (RCTs) cited for drug approvals between 2006 and August 2015 by the Food and Drug Administration, the European Medicines Agency and Health Canada. Included studies had overall survival (OS) and/or progression-free survival (PFS) primary endpoints. Meta-analyses of OS/PFS based on PS dichotomised into excellent and reduced subgroups were performed using random effects.ResultsThe systematic review identified 110 RCTs, with none reporting PS subgroup analyses for toxicity and 66 (60%) for efficacy. For these 66 RCTs involving 44 511 patients, pooled HRs for excellent and reduced groups were 0.65 (95% CI 0.61 to 0.70) and 0.67 (95% CI 0.62 to 0.72), respectively, with no difference between the two groups (p=0.68). Sensitivity analyses based on drug or cancer type and type of endpoints (OS or PFS) demonstrated similar results.ConclusionsNo decrease in relative efficacy from novel systemic therapy was found for patients with reduced PS when compared with patients with excellent PS for the range which were included in modern RCTs. Reporting of PS subgroup analyses of toxicities and more inclusion of patients with borderline low PS in RCTs should be considered for a more comprehensive understanding of the net clinical benefits of contemporary systemic therapies in patients across the spectrum of different PS.