33
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Pomalidomide with Dexamethasone for Treating Relapsed and Refractory Multiple Myeloma Previously Treated with Lenalidomide and Bortezomib: An Evidence Review Group Perspective of an NICE Single Technology Appraisal

      review-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The National Institute for Health and Care Excellence (NICE), as part of the institute’s single technology appraisal (STA) process, invited the manufacturer of pomalidomide (POM; Imnovid ®, Celgene) to submit evidence regarding the clinical and cost effectiveness of the drug in combination with dexamethasone (POM + LoDEX) for the treatment of relapsed and refractory multiple myeloma (RRMM) after at least two regimens including lenalidomide (LEN) and bortezomib (BOR). Kleijnen Systematic Reviews Ltd (KSR) and Erasmus University Rotterdam were commissioned as the Evidence Review Group (ERG) for this submission. The ERG reviewed the evidence submitted by the manufacturer, validated the manufacturer’s decision analytic model, and conducted exploratory analyses in order to assess the robustness and validity of the presented clinical and cost-effectiveness results. This paper describes the company submission, the ERG assessment, and NICE’s subsequent decisions. The company conducted a systematic review to identify studies comparing POM with comparators outlined in the NICE scope: panobinostat with bortezomib and dexamethasone (PANO + BOR + DEX), bendamustine with thalidomide and dexamethasone (BTD) and conventional chemotherapy (CC). The main clinical effectiveness evidence was obtained from MM-003, a randomized controlled trial (RCT) comparing POM + LoDEX with high-dose dexamethasone (HiDEX; used as a proxy for CC). Additional data from other studies were also used as nonrandomized observational data sources for the indirect treatment comparison of POM + LoDEX with BTD and PANO + BOR + DEX. Covariate or treatment switching adjustment methods were used for each comparison. The model developed in Microsoft ® Excel 2010 using a semi-Markov partitioned survival structure, submitted in the original submission to NICE for TA338, was adapted for the present assessment of the cost effectiveness of POM + LoDEX. Updated evidence from the clinical-effectiveness part was used for the survival modelling of progression-free survival and overall survival. For POM + LoDEX, the patient access scheme (PAS) discount was applied to the POM price. Three separate comparisons were conducted for each comparator, each comparison using a different dataset and adjustment methods. The ERG identified and corrected some errors, and the corrected incremental cost-effectiveness ratios (ICERs) for POM + LoDEX versus each comparator were presented: approximately £45,000 per quality-adjusted life-year (QALY) gained versus BTD, savings of approximately £143,000 per QALY lost versus PANO + BOR + DEX, and approximately £49,000 per QALY gained versus CC. The ERG also conducted full incremental analyses, which revealed that CC, POM + LoDEX and PANO + BOR + DEX were on the cost-effectiveness frontier. The committee’s decision on the technology under analysis deemed that POM + LoDEX should be recommended as an option for treating multiple myeloma in adults at third or subsequent relapse of treatments including both LEN and BOR, contingent on the company providing POM with the discount agreed in the PAS.

          Related collections

          Most cited references9

          • Record: found
          • Abstract: found
          • Article: not found

          International Myeloma Working Group Recommendations for the Diagnosis and Management of Myeloma-Related Renal Impairment

          The aim of the International Myeloma Working Group was to develop practical recommendations for the diagnosis and management of multiple myeloma-related renal impairment (RI).
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            PANORAMA 2: panobinostat in combination with bortezomib and dexamethasone in patients with relapsed and bortezomib-refractory myeloma.

            Panobinostat is an oral pan-deacetylase inhibitor that synergizes with bortezomib to inhibit both the aggresome and proteasome pathways in preclinical studies. PANORAMA 2 is a phase 2 trial of panobinostat in combination with bortezomib and dexamethasone to treat patients with relapsed and bortezomib-refractory multiple myeloma (with ≥2 prior lines of therapy, including an immunomodulatory drug, and patients who had progressed on or within 60 days of the last bortezomib-based therapy). Fifty-five heavily pretreated patients were enrolled (median, 4 prior regimens, including a median of 2 prior bortezomib-containing regimens). The overall response rate was 34.5% (1 near-complete response and 18 partial responses). An additional 10 patients achieved minimal response, for a clinical benefit rate of 52.7%. Median exposure and progression-free survival were 4.6 and 5.4 months, respectively. In patients who achieved a response, median time to response was 1.4 months, and median duration of response was 6.0 months. Common grade 3/4 adverse events, regardless of study drug relationship, included thrombocytopenia (63.6%), fatigue (20.0%), and diarrhea (20.0%). Only 1 patient had grade 3 peripheral neuropathy. Panobinostat, when combined with bortezomib and dexamethasone, can recapture responses in heavily pretreated, bortezomib-refractory multiple myeloma patients. This trial was registered at www.clinicaltrials.gov as #NCT01083602.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Comparison of 2 methods for calculating adjusted survival curves from proportional hazards models.

              Adjusted survival curves are often presented in medical research articles. The most commonly used method for calculating such curves is the mean of covariates method, in which average values of covariates are entered into a proportional hazards regression equation. Use of this method is widespread despite published concerns regarding the validity of resulting curves. To compare the mean of covariates method to the less widely used corrected group prognosis method in an analysis evaluating survival in patients with and without diabetes. In the latter method, a survival curve is calculated for each level of covariates, after which an average survival curve is calculated as a weighted average of the survival curves for each level of covariates. Analysis of cohort study data from 11 468 Alberta residents undergoing cardiac catheterization between January 1, 1995, and December 31, 1996. Crude and risk-adjusted survival for up to 3 years after cardiac catheterization in patients with vs without diabetes, analyzed by the mean of covariates method vs the corrected group prognosis method. According to the mean of covariates method, adjusted survival at 1044 days was 94.1% and 94.9% for patients with and without diabetes, respectively, with misleading adjusted survival curves that fell above the unadjusted curves. With the corrected group prognosis method, the corresponding survival values were 91.3% and 92.4%, with curves that fell more appropriately between the unadjusted curves. Misleading adjusted survival curves resulted from using the mean of covariates method of analysis for our data. We recommend using the corrected group prognosis method for calculating risk-adjusted curves.
                Bookmark

                Author and article information

                Contributors
                buyukkaramikli@imta.eur.nl
                Journal
                Pharmacoeconomics
                Pharmacoeconomics
                Pharmacoeconomics
                Springer International Publishing (Cham )
                1170-7690
                1179-2027
                31 October 2017
                31 October 2017
                2018
                : 36
                : 2
                : 145-159
                Affiliations
                [1 ]ISNI 0000000092621349, GRID grid.6906.9, Institute for Medical Technology Assessment (iMTA), Institute of Health Policy and Management (iBMG), , Erasmus University Rotterdam, ; Rotterdam, The Netherlands
                [2 ]ISNI 0000 0004 0450 3334, GRID grid.450936.d, Kleijnen Systematic Reviews Ltd, ; York, UK
                [3 ]ISNI 0000 0001 0481 6099, GRID grid.5012.6, Department of Family Medicine, School for Public Health and Primary Care (CAPHRI), , Maastricht University, ; Maastricht, The Netherlands
                Author information
                http://orcid.org/0000-0002-2021-9574
                Article
                581
                10.1007/s40273-017-0581-6
                5805808
                29086363
                c443104d-d6c1-403d-b635-8712b8709080
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000664, Health Technology Assessment Programme;
                Award ID: Project number 13/104/01 STA
                Categories
                Review Article
                Custom metadata
                © Springer International Publishing AG, part of Springer Nature 2018

                Economics of health & social care
                Economics of health & social care

                Comments

                Comment on this article