Evidence map›Paper›PMID 42745154›Full record

SynthesisPharmacoEconomics2026

A Systematic Review of Reporting of Validation Efforts for Cancer Health Economic Decision Models.

Pingping Li, Min Zhao, Yihe Tian, Hualing Yan, Huayu Sun, Hongchao Li

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in PharmacoEconomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Pingping Li *School of International Pharmaceutical Business, China Pharmaceutical University, Economics and Arts Building, Jiangning Campus, # 639 Longmian Avenue, Jiangning District, Nanjing, 211198, Jiangsu, China.ORCID http://orcid.org/0009-0003-1004-5739
Min Zhao *School of International Pharmaceutical Business, China Pharmaceutical University, Economics and Arts Building, Jiangning Campus, # 639 Longmian Avenue, Jiangning District, Nanjing, 211198, Jiangsu, China.ORCID http://orcid.org/0009-0003-7829-7334
Yihe TianSchool of International Pharmaceutical Business, China Pharmaceutical University, Economics and Arts Building, Jiangning Campus, # 639 Longmian Avenue, Jiangning District, Nanjing, 211198, Jiangsu, China.ORCID http://orcid.org/0009-0008-1798-4671
Hualing YanSchool of Public Health, Shanghai Jiao Tong University, Shanghai, 200025, China.ORCID http://orcid.org/0009-0005-0367-6369
Huayu SunSchool of International Pharmaceutical Business, China Pharmaceutical University, Economics and Arts Building, Jiangning Campus, # 639 Longmian Avenue, Jiangning District, Nanjing, 211198, Jiangsu, China.ORCID http://orcid.org/0009-0006-1507-0257
Hongchao LiSchool of International Pharmaceutical Business, China Pharmaceutical University, Economics and Arts Building, Jiangning Campus, # 639 Longmian Avenue, Jiangning District, Nanjing, 211198, Jiangsu, China. lihongchao@cpu.edu.cn.ORCID http://orcid.org/0000-0001-5151-9724

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study reviewed recently published cancer-related studies to identify the reporting profiles, influencing factors, and good practices of model validation efforts in health economic evaluations (HEEs).

methodsA systematic review was conducted in PubMed, Ovid MEDLINE, Ovid Embase, and ScienceDirect to retrieve recent cancer-related HEEs published between 2021 and 2026. Reporting on model validation was extracted and evaluated using the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making (ISPOR-SMDM) and Assessment of the Validation Status of Health-Economic decision models (AdViSHE) frameworks. Temporal trends, influencing factors of systematic reporting, and validation domain choices were analyzed using Fisher's exact test. We compared the observed counts of the five validation domains under two approaches: the broad-reporting ISPOR-SMDM claims versus the specific AdViSHE-verified details. Additionally, we performed a targeted analysis to identify examples of "good practice" validation in cancer HEE models.

resultsOf the 1178 identified studies, 356 (30.2%) reported model validation. Among the 356 studies, external and face validation were the most commonly reported domains (186/356 [52.2%] and 175/356 [49.2%], respectively). Only reporting proportions of internal validation and model fit showed significant increases over the past 5 years. In contrast, reporting of validation-related model adjustments significantly declined (5.0% to 1.5%), and remained the least reported transparency item (11/356, 3.1%). For the remaining domains and aspects, absolute counts rose with publication volume, but proportional reporting fluctuated, with no significant differences across years in the global tests. 43.3% (154/356) of studies included a separate validation section or reported using validation tools/guidelines. Pharmaceutical interventions and partitioned survival models were associated with lower proportions of systematic reporting. Independent and cross-validation were more frequently reported in digital health interventions (41.7% each) than in pharmaceutical ones (23.7% and 11.1%). Internal validation showed the largest under-reporting of specific details (133 studies under ISPOR-SMDM versus 56 under AdViSHE). Among selected good practice studies, the survival endpoint emerged as the most commonly used external validation measure (60.0%, 6/10).

conclusionsThe reporting proportion of validation efforts in model-based HEEs has not improved significantly over the past 5 years, although the findings reflect reporting practices rather than actual execution.

Identifiers

What Socratic holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.