Population adjusted-indirect comparisons in health technology assessment: A methodological systematic review

被引:11
作者
Truong, Bang [1 ,2 ]
Tran, Lan-Anh T. [3 ]
Le, Tuan Anh [4 ]
Pham, Thi Thu [5 ,6 ,7 ]
Vo, Tat-Thang [8 ,9 ]
机构
[1] HUTECH Univ, Fac Pharm, Ho Chi Minh City, Vietnam
[2] Auburn Univ, Dept Hlth Outcomes Res & Policy, Harrison Coll Pharm, Auburn, AL USA
[3] Univ Ghent, Dept Appl Math Comp Sci & Stat, Ghent, Belgium
[4] Katholieke Univ Leuven, Dept Biol, Leuven, Belgium
[5] Charite Univ Med Berlin, Berlin, Germany
[6] Free Univ Berlin, Berlin, Germany
[7] Humboldt Univ, Berlin, Germany
[8] Univ Penn, Wharton Sch, Dept Stat & Data Sci, Philadelphia, PA USA
[9] Univ Penn Wharton Sch, Dept Stat & Data Sci, 265 South 37th St, Philadelphia, PA 19104 USA
关键词
health technology assessment; indirect treatment comparisons; matching-adjusted indirect comparison; population adjustment; simulated treatment comparison; METAANALYSIS;
D O I
10.1002/jrsm.1653
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In health technology assessment (HTA), population-adjusted indirect comparisons (PAICs) are increasingly considered to adjust for the difference in the target population between studies. We aim to assess the conduct and reporting of PAICs in recent HTA practice, by performing, a methodological systematic review of studies implementing PAICs from PubMed, EMBASE Classic, Embase/Ovid Medline All, and Cochrane databases from January 1, 2010 to Feb 13, 2023. Four independent researchers screened the titles, abstracts, and full-texts of the identified records, then extracted data on methodological and reporting characteristics of 106 eligible articles. Most PAIC analyses (96.9%, n = 157) were conducted by (or received funding from) pharmaceutical companies. Prior to adjustment, 44.5% of analyses (n = 72) (partially) aligned the eligibility criteria of different studies to enhance the similarity of their target populations. In 37.0% of analyses (n = 60), the clinical and methodological heterogeneity across studies were extensively assessed. In 9.3% of analyses (n = 15), the quality (or bias) of individual studies was evaluated. Among 18 analyses using methods that required an outcome model specification, results of the model fitting procedure were adequately reported in three analyses (16.7%). These findings suggest that the conduct and reporting of PAICs are remarkably heterogeneous and suboptimal in current practice. More recommendations and guidelines on PAICs are thus warranted to enhance the quality of these analyses in the future.
引用
收藏
页码:660 / 670
页数:11
相关论文
共 29 条
[1]   A 25-Year Experience of US Food and Drug Administration Accelerated Approval of Malignant Hematology and Oncology Drugs and Biologics A Review [J].
Beaver, Julia A. ;
Howie, Lynn J. ;
Pelosof, Lorraine ;
Kim, Tamy ;
Liu, Jinzhong ;
Goldberg, Kirsten B. ;
Sridhara, Rajeshwari ;
Blumenthal, Gideon M. ;
Farrell, Ann T. ;
Keegan, Patricia ;
Pazdur, Richard ;
Kluetz, Paul G. .
JAMA ONCOLOGY, 2018, 4 (06) :849-856
[2]   The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials [J].
Bucher, HC ;
Guyatt, GH ;
Griffith, LE ;
Walter, SD .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 1997, 50 (06) :683-691
[3]   Second thoughts on the final rule: An analysis of baseline participant characteristics reports on ClinicalTrials.gov [J].
Cahan, Amos ;
Anand, Vibha .
PLOS ONE, 2017, 12 (11)
[4]   No Head-to-Head Trial? Simulate the Missing Arms [J].
Caro, J. Jaime ;
Ishak, K. Jack .
PHARMACOECONOMICS, 2010, 28 (10) :957-967
[5]  
Cheng D., 2019, The Statistical Performance of Matching-Adjusted Indirect Comparisons
[6]  
Degtiar I.Rose., 2021, A Review of Generalizability and Transportability
[7]   Evidence Synthesis for Decision Making 2: A Generalized Linear Modeling Framework for Pairwise and Network Meta-analysis of Randomized Controlled Trials [J].
Dias, Sofia ;
Sutton, Alex J. ;
Ades, A. E. ;
Welton, Nicky J. .
MEDICAL DECISION MAKING, 2013, 33 (05) :607-617
[8]   Regulatory approval of pharmaceuticals without a randomised controlled study: analysis of EMA and FDA approvals 1999-2014 [J].
Hatswell, Anthony J. ;
Baio, Gianluca ;
Berlin, Jesse A. ;
Irs, Alar ;
Freemantle, Nick .
BMJ OPEN, 2016, 6 (06)
[9]  
Higgins J., 2021, Cochrane Handbook for Systematic Reviews of Interventions version 6.3
[10]   Difficulties arising in reimbursement recommendations on new medicines due to inadequate reporting of population adjustment indirect comparison methods [J].
Holmes, Eileen M. ;
Leahy, Joy ;
Walsh, Cathal D. ;
White, Arthur ;
Donnan, Peter T. ;
Lamrock, Felicity .
RESEARCH SYNTHESIS METHODS, 2019, 10 (04) :615-617