Patient preferences for frontline therapies for Philadelphia chromosome-positive acute lymphoblastic leukemia: a discrete choice experiment

References

• Park HS . Current treatment strategies for Philadelphia chromosome-positive adult acute lymphoblastic leukemia. Blood Res.55(Suppl. 1), 32–36 (2020).
   Google Scholar
• Soverini S , BassanR, LionT. Treatment and monitoring of Philadelphia chromosome-positive leukemia patients: recent advances and remaining challenges. J. Hematol. Oncol.12(1), 39 (2019).
   PubMedGoogle Scholar
• Terwilliger T , Abdul-HayM. Acute lymphoblastic leukemia: a comprehensive review and 2017 update. Blood Cancer J.7(6), e577 (2017).
   PubMed Web of Science ®Google Scholar
• Chalandon Y , ThomasX, HayetteSet al. Randomized study of reduced-intensity chemotherapy combined with imatinib in adults with Ph-positive acute lymphoblastic leukemia. Blood125(24), 3711–3719 (2015).
   PubMed Web of Science ®Google Scholar
• Brown PA , ShahB, AdvaniAet al. Acute Lymphoblastic Leukemia, Version 2.2021, NCCN Clinical Practice Guidelines in Oncology. J. Natl Compr. Canc. Netw.19(9), 1079–1109 (2021).
   PubMedGoogle Scholar
• Ravandi F , O’BrienSM, CortesJEet al. Long-term follow-up of a phase 2 study of chemotherapy plus dasatinib for the initial treatment of patients with Philadelphia chromosome-positive acute lymphoblastic leukemia. Cancer121(23), 4158–4164 (2015).
   PubMed Web of Science ®Google Scholar
• Jabbour E , DerSarkissianM, DuhMSet al. Efficacy of ponatinib versus earlier generation tyrosine kinase inhibitors for front-line treatment of newly diagnosed Philadelphia-positive acute lymphoblastic leukemia. Clin. Lymphoma Myeloma Leuk.18(4), 257–265 (2018).
   PubMed Web of Science ®Google Scholar
• Sasaki K , JabbourEJ, RavandiFet al. Hyper-CVAD plus ponatinib versus hyper-CVAD plus dasatinib as frontline therapy for patients with Philadelphia chromosome-positive acute lymphoblastic leukemia: a propensity score analysis. Cancer122(23), 3650–3656 (2016).
   PubMed Web of Science ®Google Scholar
• Jabbour E , DeiningerM, HochhausA. Management of adverse events associated with tyrosine kinase inhibitors in the treatment of chronic myeloid leukemia. Leukemia25(2), 201–210 (2011).
   PubMed Web of Science ®Google Scholar
• Valent P , HadzijusufovicE, SchernthanerGH, WolfD, ReaD, le CoutreP. Vascular safety issues in CML patients treated with BCR/ABL1 kinase inhibitors. Blood125(6), 901–906 (2015).
   PubMed Web of Science ®Google Scholar
• Jabbour E , ShortNJ, RavandiFet al. Combination of hyper-CVAD with ponatinib as first-line therapy for patients with Philadelphia chromosome-positive acute lymphoblastic leukaemia: long-term follow-up of a single-centre, phase 2 study. Lancet Haematol.5(12), e618–e627 (2018).
   PubMed Web of Science ®Google Scholar
• Cortes JE , KimDW, Pinilla-IbarzJet al. A phase 2 trial of ponatinib in Philadelphia chromosome-positive leukemias. N. Engl. J. Med.369(19), 1783–1796 (2013).
   PubMed Web of Science ®Google Scholar
• Manouchehri A , KanuE, MauroMJ, AdayAW, LindnerJR, MoslehiJ. Tyrosine kinase inhibitors in leukemia and cardiovascular events: from mechanism to patient care. Arterioscler. Thromb. Vasc. Biol.40(2), 301–308 (2020).
   PubMed Web of Science ®Google Scholar
• Dahlén T , EdgrenG, LambeMet al. Cardiovascular events associated with use of tyrosine kinase inhibitors in chronic myeloid leukemia: a population-based cohort study. Ann. Intern. Med.165(3), 161–166 (2016).
   PubMed Web of Science ®Google Scholar
• Larson RA , HochhausA, HughesTPet al. Nilotinib vs imatinib in patients with newly diagnosed Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase: ENESTnd 3-year follow-up. Leukemia26(10), 2197–2203 (2012).
   PubMed Web of Science ®Google Scholar
• Cirmi S , ElAbd A, LetinierL, NavarraM, SalvoF. Cardiovascular toxicity of tyrosine kinase inhibitors used in chronic myeloid leukemia: an analysis of the FDA Adverse Event Reporting System Database (FAERS). Cancers (Basel)12(4), 826 (2020).
   PubMed Web of Science ®Google Scholar
• Levy MY , McGarryLJ, HuangH, LustgartenS, ChiroliS, IannazzoS. Benefits and risks of ponatinib versus bosutinib following treatment failure of two prior tyrosine kinase inhibitors in patients with chronic phase chronic myeloid leukemia: a matching-adjusted indirect comparison. Curr. Med. Res. Opin.35(3), 479–487 (2019).
   PubMed Web of Science ®Google Scholar
• de Bekker-Grob EW , BerlinC, LevitanBet al. Giving patients’preferences a voice in medical treatment life cycle: The PREFER public-private project. Patient10(3), 263–266 (2017).
   PubMedGoogle Scholar
• Mühlbacher AC , JuhnkeC, BeyerAR, GarnerS. Patient-focused benefit-risk analysis to inform regulatory decisions: the European Union perspective. Value Health19(6), 734–740 (2016).
   PubMed Web of Science ®Google Scholar
• Reed Johnson F , ZhouM. Patient preferences in regulatory benefit-risk assessments: a US perspective. Value Health19(6), 741–745 (2016).
   PubMed Web of Science ®Google Scholar
• European Medicines Agency . EMA Regulatory Science to 2025 (2020). www.ema.europa.eu/en/documents/regulatory-procedural-guideline/ema-regulatory-science-2025-strategic-reflection_en.pdf
   Google Scholar
• Marsh K , van TilJA, Molsen-DavidEet al. Health preference research in Europe: a review of its use in marketing authorization, reimbursement, and pricing decisions – report of the ISPOR Stated Preference Research Special Interest Group. Value Health23(7), 831–841 (2020).
   PubMed Web of Science ®Google Scholar
• Soekhai V , de Bekker-GrobEW, EllisAR, VassCM. Discrete choice experiments in health economics: past, present and future. Pharmacoeconomics37(2), 201–226 (2019).
   PubMed Web of Science ®Google Scholar
• US FDA . Patient Preference Information Voluntary Submission, Review in Premarket Approval Applications, Humanitarian Device Exemption Applications and de novo Requests, and Inclusion in Decision Summaries and Device Labeling: Guidance for Industry, Food and Drug Administration Staff, and Other Stakeholders (2016). www.fda.gov/media/92593/download
   Google Scholar
• Bridges JF , HauberAB, MarshallDet al. Conjoint analysis applications in health – a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value Health14(4), 403–413 (2011).
   PubMed Web of Science ®Google Scholar
• Reed Johnson F , LancsarE, MarshallDet al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force. Value Health16(1), 3–13 (2013).
   PubMed Web of Science ®Google Scholar
• Manski CF . The structure of random utility models. Theory Decision8, 229–254 (1977).
   Web of Science ®Google Scholar
• Marschak J . Binary choice constraints and random utility indicators (1960). In: Economic Information, Decision, and Prediction: Selected Essays: Volume I Part I Economics of Decision.Springer Netherlands, Dordrecht, The Netherlands,218–239 (1974).
   Google Scholar
• Sandorf ED . Did you miss something? Inattentive respondents in discrete choice experiments. Environ. Resour. Econ.73(4), 1197–1235 (2018).
   Web of Science ®Google Scholar
• O’Hare T , ShakespeareWC, ZhuXet al. AP24534, a pan-BCR-ABL inhibitor for chronic myeloid leukemia, potently inhibits the T315I mutant and overcomes mutation-based resistance. Cancer Cell.16(5), 401–412 (2009).
   PubMed Web of Science ®Google Scholar
• Collacott H , SoekhaiV, ThomasCet al. A systematic review of discrete choice experiments in oncology treatments. Patient14(6), 775–790 (2021).
   PubMedGoogle Scholar
• Yu PP . Challenges in measuring cost and value in oncology: making it personal. Value Health19(5), 520–524 (2016).
   PubMed Web of Science ®Google Scholar
• Mandeville KL , LagardeM, HansonK. The use of discrete choice experiments to inform health workforce policy: a systematic review. BMC Health Serv. Res.14, 367 (2014).
   PubMed Web of Science ®Google Scholar