Introduction: In prior studies, only 13-22% of lower-risk (LR) MDS pts and 11-69% of higher-risk (HR) MDS pts received potentially disease-modifying therapy despite the proven benefits of reduced blood transfusions… Click to show full abstract
Introduction: In prior studies, only 13-22% of lower-risk (LR) MDS pts and 11-69% of higher-risk (HR) MDS pts received potentially disease-modifying therapy despite the proven benefits of reduced blood transfusions and prolonged survival. Pt age, frailty, and comorbidities are commonly assumed to influence therapy choice; however, this has not been proven and other factors may govern treatment (tx) decisions. To identify factors associated with receiving first-line tx for MDS, health services data from the Connect® MDS/AML Registry, which includes MDS pts treated in US academic, community, and government-based centers, were analyzed. Methods: The Connect MDS/AML Registry (NCT01688011) is an ongoing, prospective observational cohort study of pts with newly diagnosed acute myeloid leukemia (AML) (aged ≥ 55 years) or MDS (aged ≥ 18 years). Local AML and MDS diagnoses are confirmed by an independent central review of all available diagnostic reports. Baseline demographics, disease characteristics, laboratory parameters, and ZIP-code-level per capita income were collected at enrollment on MDS pts from December 2013 to March 2018. Analyses were performed separately for LR-MDS pts, defined as having Low- or Intermediate (Int)-1-risk MDS according to the International Prognostic Scoring System (IPSS), and HR-MDS pts, defined as having Int-2- or High-risk MDS. Uni- and multivariable logistic regression analyses were used to identify factors associated with early use of first-line tx in MDS pts, defined as chemotherapy or biotherapy initiated ≤ 45 days after diagnosis. Univariable testing was performed for each potential predictor; those with an association of P < 0.15 were included in multivariable analysis. The final multivariable model was derived using a score-based selection method. Pts receiving first-line tx (regardless of intensity) were compared with a combined group of pts receiving best supportive care (BSC) or no tx. Results: As of March 8, 2018, data from 536 MDS pts (232 HR-MDS and 304 LR-MDS) from 130 institutions (20 academic and 110 community/government) were available for analysis. In the LR-MDS group, median age was 76 years (range 28-95), with 65% male, and 89% white; 19% had private insurance, and the average median ZIP-code-level per capita income was $28,000 ($10,000-$92,000). In the HR-MDS group, median age was 73 years (range 19-94), with 67% male and 86% white; 23% had private insurance, and the average median ZIP-code-level per capita income was $26,000 (range $14,000-$83,000). In LR-MDS pts, univariable predictors of early first-line therapy initiation included baseline transfusion dependency (defined as ≥ 1 transfusion episode in the 8 weeks prior to diagnosis), comorbidities (higher Adult Comorbidity Evaluation 27 [ACE-27] score), having fluorescence in situ hybridization (FISH) or molecular analyses performed, Int-1 IPSS risk score, primary vs secondary MDS, and higher bone marrow (BM) blast percentage. Multivariable logistic regression analysis identified transfusion dependency (P = 0.001), Int-1 IPSS risk score (P = 0.026), BM blast percentage ≥ 5% (P = 0.002), and having both FISH and molecular genetic testing performed at diagnosis (P = 0.022) as factors significantly associated with early initiation of first-line tx (Table 1). Univariable analysis of HR-MDS pts showed insurance status, comorbidities (ACE-27 score ≤ 2), High IPSS risk score, primary vs secondary MDS, having flow cytometry analysis performed, lower baseline frailty, and BM blast percentage as univariable correlates associated with early tx. Multivariable logistic regression analysis identified private insurance coverage (P = 0.031) and BM blast percentage ≥ 10% (P = 0.021) as factors significantly associated with early initiation of first-line tx (Table 2). Conclusions: Early first-line tx in MDS pts was significantly associated with disease severity as indicated by transfusion dependency, higher IPSS risk score, and higher BM blast percentage. However, counter to common assumptions, age, frailty, and comorbidities were not associated with receiving early tx in MDS. Access to care may be an important factor in the tx of MDS pts, as having private health insurance and undergoing genetic testing were also significantly associated with receiving early tx. Additional pt-centered research with prescribing MDS physicians as stakeholders is needed to verify and extend these findings. Cogle: Celgene: Other: Steering Committee Member of Connect MDS/AML Registry. Grinblatt:Celgene: Membership on an entity's Board of Directors or advisory committees; Alexion: Speakers Bureau; AbbVie: Consultancy. Komrokji:Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding. Savona:Boehringer Ingelheim: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding. Scott:Celgene: Consultancy, Honoraria, Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees. Louis:Cellmedica: Patents & Royalties; Celgene: Employment. Flick:Celgene: Employment. Nifenecker:Celgene: Employment. Kiselev:Celgene: Employment, Equity Ownership. Swern:Celgene: Employment, Equity Ownership. Steensma:Takeda: Consultancy; Syros: Research Funding; Otsuka: Membership on an entity's Board of Directors or advisory committees; Onconova: Consultancy; Novartis: Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding; Janssen: Consultancy, Research Funding; H3 Biosciences: Research Funding; Celgene: Research Funding; Amphivena: Membership on an entity's Board of Directors or advisory committees; Acceleron: Consultancy.
               
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