PMID- 27325334
OWN - NLM
STAT- MEDLINE
DCOM- 20170517
LR  - 20170517
IS  - 1524-4733 (Electronic)
IS  - 1098-3015 (Linking)
VI  - 19
IP  - 4
DP  - 2016 Jun
TI  - Decisions on Further Research for Predictive Biomarkers of High-Dose Alkylating 
      Chemotherapy in Triple-Negative Breast Cancer: A Value of Information Analysis.
PG  - 419-30
LID - S1098-3015(16)00021-8 [pii]
LID - 10.1016/j.jval.2016.01.015 [doi]
AB  - OBJECTIVES: To inform decisions about the design and priority of further studies 
      of emerging predictive biomarkers of high-dose alkylating chemotherapy (HDAC) in 
      triple-negative breast cancer (TNBC) using value-of-information analysis. 
      METHODS: A state transition model compared treating women with TNBC with current 
      clinical practice and four biomarker strategies to personalize HDAC: 1) 
      BRCA1-like profile by array comparative genomic hybridization (aCGH) testing; 2) 
      BRCA1-like profile by multiplex ligation-dependent probe amplification (MLPA) 
      testing; 3) strategy 1 followed by X-inactive specific transcript gene (XIST) and 
      tumor suppressor p53 binding protein (53BP1) testing; and 4) strategy 2 followed 
      by XIST and 53BP1 testing, from a Dutch societal perspective and a 20-year time 
      horizon. Input data came from literature and expert opinions. We assessed the 
      expected value of partial perfect information, the expected value of sample 
      information, and the expected net benefit of sampling for potential ancillary 
      studies of an ongoing randomized controlled trial (RCT; NCT01057069). RESULTS: 
      The expected value of partial perfect information indicated that further research 
      should be prioritized to the parameter group including "biomarkers' prevalence, 
      positive predictive value (PPV), and treatment response rates (TRRs) in 
      biomarker-negative patients and patients with TNBC" (euro639 million), followed by 
      utilities (euro48 million), costs (euro40 million), and transition probabilities (TPs) 
      (euro30 million). By setting up four ancillary studies to the ongoing RCT, data on 
      1) TP and MLPA prevalence, PPV, and TRR; 2) aCGH and aCGH/MLPA plus XIST and 
      53BP1 prevalence, PPV, and TRR; 3) utilities; and 4) costs could be 
      simultaneously collected (optimal size = 3000). CONCLUSIONS: Further research on 
      predictive biomarkers for HDAC should focus on gathering data on TPs, prevalence, 
      PPV, TRRs, utilities, and costs from the four ancillary studies to the ongoing 
      RCT.
CI  - Copyright (c) 2016 International Society for Pharmacoeconomics and Outcomes 
      Research (ISPOR). Published by Elsevier Inc. All rights reserved.
FAU - Miquel-Cases, Anna
AU  - Miquel-Cases A
AD  - Department of Psychosocial Research and Epidemiology, Netherlands Cancer 
      Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Amsterdam, The Netherlands.
FAU - Retel, Valesca P
AU  - Retel VP
AD  - Department of Psychosocial Research and Epidemiology, Netherlands Cancer 
      Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Amsterdam, The Netherlands.
FAU - van Harten, Wim H
AU  - van Harten WH
AD  - Department of Psychosocial Research and Epidemiology, Netherlands Cancer 
      Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Amsterdam, The Netherlands; 
      Department of Health Technology and Services Research, University of Twente, 
      Enschede, The Netherlands. Electronic address: w.v.harten@nki.nl.
FAU - Steuten, Lotte M G
AU  - Steuten LM
AD  - Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer 
      Research Center, Seattle, WA, USA.
LA  - eng
SI  - ClinicalTrials.gov/NCT01057069
PT  - Comparative Study
PT  - Journal Article
DEP - 20160406
PL  - United States
TA  - Value Health
JT  - Value in health : the journal of the International Society for Pharmacoeconomics 
      and Outcomes Research
JID - 100883818
RN  - 0 (Alkylating Agents)
RN  - 0 (Antineoplastic Agents)
RN  - 0 (Biomarkers, Tumor)
RN  - 0 (RNA, Long Noncoding)
RN  - 0 (TP53BP1 protein, human)
RN  - 0 (Tumor Suppressor p53-Binding Protein 1)
RN  - 0 (XIST non-coding RNA)
RN  - EC 2.3.2.27 (BRAP protein, human)
RN  - EC 2.3.2.27 (Ubiquitin-Protein Ligases)
SB  - IM
MH  - Adult
MH  - Alkylating Agents/economics/therapeutic use
MH  - Antineoplastic Agents/economics/therapeutic use
MH  - Biomarkers, Tumor/*economics
MH  - Cost-Benefit Analysis
MH  - Decision Support Techniques
MH  - Disease-Free Survival
MH  - Female
MH  - Health Priorities/economics
MH  - Humans
MH  - Markov Chains
MH  - Middle Aged
MH  - Netherlands/epidemiology
MH  - RNA, Long Noncoding
MH  - Randomized Controlled Trials as Topic
MH  - Research/economics
MH  - Triple Negative Breast Neoplasms/drug therapy/*economics/epidemiology/therapy
MH  - Tumor Suppressor p53-Binding Protein 1
MH  - Ubiquitin-Protein Ligases/*economics/genetics
OTO - NOTNLM
OT  - decision modeling
OT  - diagnostics
OT  - high-dose alkylating chemotherapy
OT  - predictive biomarkers
OT  - value of information
EDAT- 2016/06/22 06:00
MHDA- 2017/05/18 06:00
CRDT- 2016/06/22 06:00
PHST- 2015/01/06 00:00 [received]
PHST- 2016/01/28 00:00 [revised]
PHST- 2016/01/31 00:00 [accepted]
PHST- 2016/06/22 06:00 [entrez]
PHST- 2016/06/22 06:00 [pubmed]
PHST- 2017/05/18 06:00 [medline]
AID - S1098-3015(16)00021-8 [pii]
AID - 10.1016/j.jval.2016.01.015 [doi]
PST - ppublish
SO  - Value Health. 2016 Jun;19(4):419-30. doi: 10.1016/j.jval.2016.01.015. Epub 2016 
      Apr 6.