Error propagation in simulated treatment comparisons for multiple myeloma: Results from a simulation.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e20523-e20523
Author(s):  
Eric Mackay ◽  
Justin Slater ◽  
Paul Arora ◽  
Kristian Thorlund ◽  
Audrey Beliveau ◽  
...  

e20523 Background: Comparing the effectiveness of multiple myeloma treatments presents a challenge due to the limited number of head-to-head trials with which to conduct indirect treatment comparisons. This is particularly true when subgroup analysis is of interest. In comparative effectiveness research Simulated Treatment Comparisons (STCs) are becoming increasingly common in the absence of head-to-head trials. STCs use estimates from limited IPD to adjust for covariate imbalance between trials, however the uncertainty from these estimates is generally ignored when estimating relative treatment effects. This study demonstrates the need to account for this uncertainty when conducting STCs for indications such as multiple myeloma. We introduce an STC method that accounts for the uncertainty due to covariate adjustment, and demonstrate its effectiveness via simulation. Methods: We simulated two single arm studies (N = 300 for both), each containing age and overall survival. We assume study 1 has individual patient data available, and study 2 only has aggregate age data and a digitized Kaplan-Meier curve. We compute a covariate adjustment term based on the mean age difference between the studies and the age coefficients from fitting a parametric survival model to the observed study 1 IPD. We then estimate the variance of this adjustment term via bootstrapping and incorporate this uncertainty into a Bayesian STC model which estimates the relative treatment effect for the two study datasets converted to a digitized Kaplan-Meier format. Results: The proportion of 95% credible intervals (CrI) that captured the true treatment effect was 86.8% without error propagation, whereas 92.0% of CrI’s captured the true treatment with error propagation. 94.9% of CrI’s contained the true treatment effect when using survival regression with the complete IPD. Conclusions: Failing to account for uncertainty from the covariate adjustment when conducting simulated treatment comparisons generally leads to underestimating the uncertainty of the relative treatment effect. This method better captures the uncertainty introduced when conducting an STC and has the potential to yield more reliable estimates of the comparative effectiveness of multiple myeloma treatments.

Author(s):  
Faith Davies ◽  
Robert Rifkin ◽  
Caitlin Costello ◽  
Gareth Morgan ◽  
Saad Usmani ◽  
...  

AbstractMultiple available combinations of proteasome inhibitors, immunomodulators (IMIDs), and monoclonal antibodies are shifting the relapsed/refractory multiple myeloma (RRMM) treatment landscape. Lack of head-to-head trials of triplet regimens highlights the need for real-world (RW) evidence. We conducted an RW comparative effectiveness analysis of bortezomib (V), carfilzomib (K), ixazomib (I), and daratumumab (D) combined with either lenalidomide or pomalidomide plus dexamethasone (Rd or Pd) in RRMM. A retrospective cohort of patients initiating triplet regimens in line of therapy (LOT) ≥ 2 on/after 1/1/2014 was followed between 1/2007 and 3/2018 in Optum’s deidentified US electronic health records database. Time to next treatment (TTNT) was estimated using Kaplan-Meier methods; regimens were compared using covariate-adjusted Cox proportional hazard models. Seven hundred forty-one patients (820 patient LOTs) with an Rd backbone (VRd, n = 349; KRd, n = 218; DRd, n = 99; IRd, n = 154) and 348 patients (392 patient LOTs) with a Pd backbone (VPd, n = 52; KPd, n = 146; DPd, n = 149; IPd, n = 45) in LOTs ≥2 were identified. More patients ≥75 years received IRd (39.6%), IPd (37.8%), and VRd (36.7%) than other triplets. More patients receiving VRd/VPd were in LOT2 vs other triplets. Unadjusted median TTNT in LOT ≥ 2: VRd, 13.9; KRd, 8.7; IRd, 11.4; DRd, not estimable (NE); and VPd, 12.0; KPd, 6.7; IPd, 9.5 months; DPd, NE. In covariate-adjusted analysis, only KRd vs DRd was associated with a significantly higher risk of next LOT initiation/death (HR 1.72; P = 0.0142); no Pd triplet was significantly different vs DPd in LOT ≥ 2. Our data highlight important efficacy/effectiveness gaps between results observed in phase 3 clinical trials and those realized in the RW.


2021 ◽  
pp. 107815522199553
Author(s):  
Joshua Richter ◽  
Vamshi Ruthwik Anupindi ◽  
Jason Yeaw ◽  
Suneel Kudaravalli ◽  
Stojan Zavisic ◽  
...  

Introduction Real-world evidence on later line treatment of relapsed/refractory multiple myeloma (RRMM) is sparse. We evaluated clinical outcomes among RRMM patients in the 1-year following treatment with pomalidomide or daratumumab and compared economic outcomes between RRMM patients and non-MM patients. Patient and Methods Adult patients with ≥1 claim of pomalidomide or daratumumab were identified between January 2012 and February 2018 using IQVIA PharMetrics® Plus US claims database. Patients were required to have a diagnosis or treatment for MM and a claim of any immunomodulatory drugs and proteasome inhibitors before the index date. Mean time to new therapy, overall survival (OS) using Kaplan-Meier curve and adverse events (AEs) were reported over the 1-year post-index period. RRMM patients were also matched to a non-MM comparator cohort and economic outcomes were compared between the two cohorts. Results 289 RRMM patients were matched to 1,445 patients without MM. Most prevalent hematological AE was anemia (72.0%) and non-hematological AE was infections (75.4%). Mean (SD) time to a new treatment was 4.7 (5.3) months and median OS was 14.6 months. RRMM patients had significantly higher hospitalizations and physician office visits (Both P < .0001) compared to non-MM patients. Adjusting for baseline characteristics, patients with RRMM had 4.9 times (95% CI 3.8-6.4, P < .0001) the total healthcare costs compared with patients without MM. The major driver of total costs among RRMM patients was pharmacy costs (67.3%). Conclusion RRMM patients showed a high frequency of AEs, low OS, and a substantial economic burden suggesting need for effective treatment options.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Steve Kanters ◽  
Mohammad Ehsanul Karim ◽  
Kristian Thorlund ◽  
Aslam Anis ◽  
Nick Bansback

Abstract Background The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. Methods Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. Results Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. Conclusions Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1149-1150
Author(s):  
L. Gossec ◽  
S. Siebert ◽  
P. Bergmans ◽  
K. De Vlam ◽  
E. Gremese ◽  
...  

Background:Several biologic DMARDs (bDMARDs) exist for PsA, TNFi and UST being the earliest on European markets. When bDMARDs are insufficiently effective, later-line bDMARDs typically have shorter persistence. Treatment persistence reflects a mix of effectiveness and adverse events (AEs), and persistence data are limited in PsA.Objectives:Comparative analysis of 1-year persistence of UST and TNFi within the prospective PsABio cohort.Methods:PsABio is an observational, multinational study of PsA patients (pts) treated with 1st to 3rd line UST or TNFi at their rheumatologist’s discretion.1Treatment persistence (up to 15 months of follow-up) was defined as time between start of first bDMARD treatment in PsABio, and either stop or switch to another bDMARD, or withdrawal.Persistence of UST and TNFi is shown by Kaplan-Meier curves and compared using Cox regression analysis, with propensity score (PS) to adjust for baseline imbalanced demographic and disease-related covariates (age, sex, bDMARD line, BMI, Clinical Disease Activity index for PSoriatic Arthritis [cDAPSA], 12-item PsA Impact of Disease [PsAID-12], Fibromyalgia Rapid Screening Tool [FiRST] score, co-treatments with MTX, NSAIDs, glucocorticoids, cardiovascular/metabolic comorbidities, dactylitis, enthesitis and body surface area [BSA]). Factors including concomitant MTX use and skin involvement: <3%, 3–10% and >10%, were added to the Cox model to investigate their impact on the PS-adjusted treatment effect.Results:Of 438 and 455 pts who started UST and TNF, respectively, 121 (28%) and 134 (29%) stopped or switched treatment before Month 15, with differences (as expected) according to treatment line (Fig. 1a, b). Reasons for stop/switch were related to safety/AEs in 12% (UST) and 28% (TNFi), and effectiveness (joints, nails or skin) in 77% (UST) and 69% (TNFi) of pts.The observed mean time on drug was 397 days for UST and 385 days for TNFi pts (1st line 410/397 days, 2nd 390/382 days, 3rd 381/338 days). Fig. 1b shows similar persistence for all drugs and treatment lines, except for lower persistence in TNFi 3rd line vs 1st/2nd. In PS-adjusted Cox analysis, no statistically significant difference between UST and TNFi persistence was seen; hazard ratio (HR; 95% CI) for stop/switch bDMARD (UST vs TNFi) was 0.82 (0.60, 1.13). In the model, bDMARD monotherapy (without MTX) and extensive skin involvement (BSA >10%), showed significantly better persistence for UST (HR 0.61 [0.42, 0.90] and 0.41 [0.19, 0.89] respectively; unadjusted Kaplan-Meier graphs shown in Fig. 1c, d). MTX co-therapy and low BSA did not affect the PS-adjusted treatment effect. Other factors added to the PS-adjusted Cox model did not show significant effects.Conclusion:In this real-world PsA cohort undergoing bDMARD treatment, persistence was generally comparable for UST and TNFi, but some clinical situations led to better drug persistence with UST compared to TNFi – particularly monotherapy, more extensive skin involvement, and in 3rd-line treatment. Our data emphasise the importance of skin involvement for pts with PsA.References:[1]Gossec L, et al.Ann Rheum Dis. 2018;77(suppl 2):Abstract AB0928Acknowledgments:This study was funded by Janssen.Disclosure of Interests:Laure Gossec Grant/research support from: Lilly, Mylan, Pfizer, Sandoz, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis, UCB, Stefan Siebert Grant/research support from: BMS, Boehringer Ingelheim, Celgene, GlaxoSmithKline, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Boehringer Ingelheim, Janssen, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, Celgene, Janssen, Novartis, Paul Bergmans Shareholder of: Johnson & Johnson, Employee of: Janssen, Kurt de Vlam Consultant of: Celgene Corporation, Eli Lilly, Novartis, Pfizer, UCB – consultant, Speakers bureau: Celgene Corporation, Eli Lilly, Novartis, Pfizer, UCB – speakers bureau and honoraria, Elisa Gremese Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Novartis, Sanofi, UCB, Roche, Pfizer, Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Novartis, Sanofi, UCB, Roche, Pfizer, Beatriz Joven-Ibáñez Speakers bureau: Abbvie, Celgene, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Tatiana Korotaeva Grant/research support from: Pfizer, Consultant of: Abbvie, BIOCAD, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Novartis, Novartis-Sandoz, Pfizer, UCB, Speakers bureau: Abbvie, BIOCAD, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Novartis, Novartis-Sandoz, Pfizer, UCB, Wim Noel Employee of: Janssen Pharmaceuticals NV, Michael T Nurmohamed Grant/research support from: Abbvie, Bristol-Myers Squibb, Celltrion, GlaxoSmithKline, Jansen, Eli Lilly, Menarini, Merck Sharp & Dohme, Mundipharma, Pfizer, Roche, Sanofi, USB, Consultant of: Abbvie, Bristol-Myers Squibb, Celltrion, GlaxoSmithKline, Jansen, Eli Lilly, Menarini, Merck Sharp & Dohme, Mundipharma, Pfizer, Roche, Sanofi, USB, Speakers bureau: Abbvie, Bristol-Myers Squibb, Celltrion, GlaxoSmithKline, Jansen, Eli Lilly, Menarini, Merck Sharp & Dohme, Mundipharma, Pfizer, Roche, Sanofi, USB, Petros Sfikakis Grant/research support from: Grant/research support from Abvie, Novartis, MSD, Actelion, Amgen, Pfizer, Janssen Pharmaceutical, UCB, Elke Theander Employee of: Janssen-Cilag Sweden AB, Josef S. Smolen Grant/research support from: AbbVie, AstraZeneca, Celgene, Celltrion, Chugai, Eli Lilly, Gilead, ILTOO, Janssen, Novartis-Sandoz, Pfizer Inc, Samsung, Sanofi, Consultant of: AbbVie, AstraZeneca, Celgene, Celltrion, Chugai, Eli Lilly, Gilead, ILTOO, Janssen, Novartis-Sandoz, Pfizer Inc, Samsung, Sanofi


RMD Open ◽  
2018 ◽  
Vol 4 (2) ◽  
pp. e000809 ◽  
Author(s):  
Kim Lauper ◽  
Denis Mongin ◽  
Florenzo Iannone ◽  
Eirik Klami Kristianslund ◽  
Tore K Kvien ◽  
...  

ObjectiveTo compare the real-word effectiveness of subcutaneous tocilizumab (TCZ-SC) and intravenous tocilizumab (TCZ-IV) in rheumatoid arthritis (RA).MethodsPatients with RA with TCZ from eight European registries were included. Drug retention was compared using unadjusted Kaplan-Meier and Cox models adjusted for baseline patient, disease and treatment characteristics, using a strata term for year of treatment initiation and country of registry. The proportions of patients achieving Clinical Disease Activity Index (CDAI) remission and low disease activity (LDA) at 1 year were compared using samples matched on the same covariates and corrected for attrition using LUNDEX.Results3448 patients were retrieved, 2414 with TCZ-IV and 1034 with TCZ-SC. Crude median retention was 3.52 years (95% CI 3.22 to 3.85) for TCZ-IV and 2.12 years for TCZ-SC (95% CI 1.88 to 2.38). In a country-stratified and year of treatment initiation–stratified, covariate-adjusted analysis, hazards of discontinuation were similar between TCZ-SC and TCZ-IV treated patients (HR 0.93, 95% CI 0.80 to 1.09). The average adjusted CDAI change at 1 year was similar in both groups (−6.08). After matching, with 560 patients in each group, CDAI remission corrected for attrition at 1 year was also similar between TCZ-SC and TCZ-IV (10.4% in TCZ-IV vs 12.8% in TCZ-SC (difference: 2.4%, bootstrap 95% CI −2.1% to 7.6%)), but CDAI LDA was lower in TCZ-IV patients: 41.0% in TCZ-IV versus 49.1% in TCZ-SC (difference: 8.0 %; bootstrap 95% CI 2.4% to 12.4%).ConclusionWith similar retention and effectiveness, TCZ-SC is an adequate alternative to TCZ-IV for RA. When possible, considering the costs of the TCZ-IV route, TCZ-SC should be the preferred mode of administration.


2013 ◽  
Vol 1 (1) ◽  
pp. 135-154 ◽  
Author(s):  
Peter M. Aronow ◽  
Joel A. Middleton

AbstractWe derive a class of design-based estimators for the average treatment effect that are unbiased whenever the treatment assignment process is known. We generalize these estimators to include unbiased covariate adjustment using any model for outcomes that the analyst chooses. We then provide expressions and conservative estimators for the variance of the proposed estimators.


2018 ◽  
Vol 7 (8) ◽  
pp. 797-805 ◽  
Author(s):  
Michael L Sabolinski ◽  
Gary Gibbons

Aim: To compare the effectiveness of bilayered living cellular construct (BLCC) and an acellular fetal bovine collagen dressing (FBCD) for the treatment of venous leg ulcers. Methods: Data from WoundExpert® (Net Health, PA, USA) was used to analyze 1021 refractory venous leg ulcers treated at 177 facilities. Results: Kaplan–Meier analyses showed that BLCC (893 wounds) was superior to FBCD (128 wounds), p = 0.01 for: wound closure by weeks 12 (31 vs 25%), 24 (55 vs 43%) and 36 (68 vs 53%); reduction in time to wound closure of 37%, (19 vs 30 weeks); and improvement in the probability of healing by 45%. Conclusion: BLC versus FBCD showed significant differences in both time to and frequency of healing suggesting that BLCC may provide significant cost savings compared with FBCD.


2018 ◽  
Vol 10 (04) ◽  
pp. 363-369 ◽  
Author(s):  
Serife Solmaz ◽  
Ozcan Uzun ◽  
Celal Acar ◽  
Omur Gokmen Sevindik ◽  
Ozden Piskin ◽  
...  

ABSTRACT BACKGROUND: Recent reports showed neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR), as a predictor of progression-free survival (PFS) and overall survival (OS) in various malignancies. MATERIALS AND METHODS: We retrospectively examined the PLR, NLR, and MLR in a cohort of 186 newly diagnosed multiple myeloma (MM) patients. This study investigated the prognostic relevance of NLR, PLR, and MLR in MM patients. NLR, PLR, and MLR were calculated from whole blood counts before therapy. The Kaplan–Meier curves and multivariate Cox models were used for the evaluation of survival. RESULTS: Applying cutoff of 1.9 (NLR), 120.00 (PLR), and 0.27 (MLR), decreased PLR showed a negative impact on the outcome. Decreased PLR is an independent predictor for PFS and OS. There were no significant differences in median survival between the high and low NLR (P = 0.80) and MLR (P = 0.87) groups. CONCLUSIONS: In this study, thrombocytopenia and low PLR are associated with poor survival in MM patients does this P value apply to thrombocytopenia or low PLR and may serve as the cost-effective prognostic biomarker.


2020 ◽  
Vol 23 ◽  
pp. S8
Author(s):  
E. Mackay ◽  
J. Slater ◽  
P. Arora ◽  
K. Thorlund ◽  
A. Beliveau ◽  
...  

Biometrics ◽  
2019 ◽  
Vol 76 (2) ◽  
pp. 664-669
Author(s):  
Jiannan Lu ◽  
Yunshu Zhang ◽  
Peng Ding

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