We set out an analytical strategy to examine variations in resource use, whether cost or length of stay, of patients hospitalised with different conditions. The methods are designed to evaluate (i) how well diagnosis-related groups (DRGs) capture variation in resource use relative to other patient characteristics and (ii) what influence the hospital has on their resource use. In a first step, we examine the influence of variables that describe each individual patient, including the DRG to which the patients are assigned and a range of personal and treatment-related characteristics. In a second step, we explore the influence that hospitals have on the average cost or length of stay of their patients, purged of the influence of the variables accounted for in the first stage. We provide a rationale for the variables used in both stages of the analysis and detail how each is defined. The analytical strategy allows us (i) to identify those factors that explain variation in resource use across patients, (ii) to assess the explanatory power of DRGs relative to other patient and treatment characteristics and (iii) to assess relative hospital performance in managing resources and the characteristics of hospitals that explain this performance.

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Introduction: Daratumumab, a human IgGκ monoclonal antibody targeting CD38 with a direct on-tumor and immunomodulatory mechanism of action, is approved in combination with standard-of-care regimens for the treatment of newly diagnosed multiple myeloma (NDMM) and RRMM. When combined with standard of care regimens across four phase 3 studies, daratumumab demonstrated ≥44% reductions in the risk of progression or death, nearly doubled complete response (CR) or better rates, and tripled minimal residual disease (MRD)-negative rates at the 10-5 sensitivity threshold in pts with RRMM or NDMM (Palumbo A, et al. N Engl J Med 2016. 375[8]:754-766; Dimopoulos MA, et al. N Engl J Med 2016. 375[14]:1319-1331; Mateos MV, et al. N Engl J Med 2018. 378[6]:518-528; Facon T, et al. N Engl J Med 2019. 380[22]2104-2015). In the phase 3 POLLUX study (median follow-up 44.3 months), D-Rd reduced the risk of disease progression or death by 56% and significantly increased the overall response rate (ORR) versus Rd alone (93% vs 76%; P <0.0001) in patients (pts) with RRMM. Here, we present updated efficacy and safety analyses of POLLUX after >4 years of median follow-up. Methods: Pts who received ≥1 prior line of therapy were randomized (1:1) to Rd (lenalidomide 25 mg PO on Days 1-21 of each 28-day cycle; dexamethasone 40 mg per week) ± daratumumab (16 mg/kg IV QW for Cycles 1-2, Q2W for Cycles 3-6, then Q4W until disease progression). Cytogenetic risk was determined by local fluorescence in situ hybridization or karyotyping; pts with high cytogenetic risk had t(4;14), t(14;16), and del17p abnormalities. PFS on subsequent line of therapy (PFS2), an exploratory endpoint, was defined as time from randomization to progression after next line of subsequent therapy or death. Results: A total of 569 pts were randomized (D-Rd, n = 286; Rd, n = 283). At a median follow-up of 51.3 months, D-Rd significantly prolonged progression-free survival (PFS) versus Rd (median 45.8 vs 17.5 months; hazard ratio [HR], 0.43; 95% confidence interval [CI], 0.35-0.54; P <0.0001; Figure). D-Rd also prolonged PFS versus Rd among pts with 1 prior line of therapy, among pts with 1-3 prior lines of therapy, and regardless of cytogenetic risk status (Table). A PFS benefit with D-Rd was also observed among pts who received prior lenalidomide (median 38.8 vs 18.6 months; HR, 0.34; 95% CI, 0.19-0.59; P <0.0001) and among pts refractory to bortezomib (median 34.3 vs 11.3 months; HR, 0.41; 95% CI, 0.25-0.68; P = 0.0004). D-Rd was associated with a significantly higher ORR versus Rd (93% vs 76%), including higher rates of ≥very good partial response (81% vs 49%) and ≥CR (57% vs 24%; all P <0.0001). Median time to next therapy for D-Rd versus Rd was not reached in the D-Rd group versus 22.8 months in the Rd group (HR, 0.39; 95% CI, 0.30-0.49; P <0.0001). D-Rd significantly prolonged PFS2 versus Rd (median 53.3 vs 31.6 months; HR, 0.54; 95% CI, 0.43-0.68; P <0.0001). In the D-Rd group, 121 deaths were observed versus 133 deaths in the Rd group; follow-up for overall survival is ongoing. The median duration of treatment was 34.3 months in the D-Rd arm versus 16.0 months in the Rd arm. The most common (≥10%) grade 3/4 treatment-emergent adverse events (TEAEs) observed with D-Rd versus Rd included neutropenia (56% vs 42%), anemia (18% vs 22%), thrombocytopenia (15% vs 16%), pneumonia (16% vs 10%), and diarrhea (10% vs 4%). Similar rates of discontinuations due to TEAEs were observed for D-Rd versus Rd (16% vs 15%). The incidence of invasive second primary malignancies was 4.9% and 5.7% for the D-Rd and Rd groups, respectively. Additional efficacy data, including minimal residual disease, and safety analyses will be presented at the meeting. Conclusion: After >4 years of median follow-up, D-Rd continues to demonstrate a significant PFS benefit and higher rates of deeper responses versus Rd alone in pts with RRMM. Although significant PFS benefit was observed with D-Rd in RRMM pts regardless of prior lines of therapy or cytogenetic risk status, the greatest benefit was observed when used in patients treated earlier with D-Rd. The significant improvement in PFS2 suggests a potential survival benefit, but OS data is still immature. No new safety concerns were identified with this additional follow-up. Disclosures Kaufman: Celgene: Consultancy; Winship Cancer Institute of Emory University: Employment; Takeda: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; AbbVie: Consultancy; Bristol-Myers Squibb: Consultancy; Incyte: Consultancy; Karyopharm: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy; Amgen: Consultancy. Usmani:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, SkylineDX, Takeda: Other: Consultant/Advisor; Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau; Amgen Array Biopharma, Bristol-Myers Squibb, Celgene, Janssen, Merck, Pharmacyclics, Sanofi, Takeda: Other: Research Grant. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Bahlis:Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. White:Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria. Cook:Amgen, Bristol-Myers Squib, GlycoMimetics, Seattle Genetics, Sanofi: Honoraria; Janssen, Takeda, Sanofi, Karyopharm, Celgene: Consultancy, Honoraria, Speakers Bureau; Celgene, Janssen-Cilag, Takeda: Honoraria, Research Funding. Ho:Novartis: Other: Trial Investigator meeting travel costs; La Jolla: Other: Trial Investigator meeting travel costs; Janssen: Other: Trial Investigator meeting travel costs; Celgene: Other: Trial Investigator meeting travel costs. Moreau:Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Krevvata:Janssen: Employment. Pei:Janssen: Employment, Equity Ownership. Ukropec:Janssen: Employment, Equity Ownership. Renaud:Janssen: Employment, Equity Ownership. Trivedi:Janssen: Employment, Equity Ownership. Kobos:Janssen: Employment. Dimopoulos:Sanofi Oncology: Research Funding.

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Much research in France or abroad has highlighted the medical practice variation (MPV) phenomenon. There is no consensus on the origin of MPV between preference-centered approaches versus opportunities and constraints approaches. This study's main purpose is to assess the relevance of hypotheses which assume that physicians adopt a uniform practice style for their patients for each similar clinical decision in a context of medical decision with low uncertainty and professional practice with weak regulation. Multilevel models are evaluated: first to measure variability of antibiotics prescription by French general practitioners (GPs) for acute rhinopharyngitis regarding clinical guidelines, and to test its significance in order to determine to what extent prescription differences are due to between or within GPs discrepancies; second, to prioritize its determinants, especially those relating to a GP or his/her practice setting environment, while controlling visit or patient confounders. The study was based on 2001 activity data, along with an ad hoc questionnaire, of a sample of 778 GP taken from a panel of 1006 computerized French GPs. We observed that a large part of the total variation was due to intra-physician variability (70%). It is patient characteristics that largely explain the prescription, even if GP or practice setting characteristics (location, level of activity, network participation, continuing medical education) and environmental factors (visit from pharmaceutical sales representatives) also exert considerable influence. This suggests that MPV are partly caused by differences in the type of dissemination of medical information and this may help policy makers to identify and develop facilitators for promoting better use of antibiotics in France and, more generally, for influencing GP practices when it is of interest.