Evidence map›Paper›PMID 41832310›Full record

ArticleTherapeutic innovation & regulatory science2026

Research on the Quality Evaluation Indicators of Real-World Data in the Review of Anti-Tumor Drugs for Chinese Regulatory Frameworks.

Jie-Ying Zhang, Yong Tang, Fang-Zheng Dong, Ning-Ying Mao, Jun Li

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Article in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jie-Ying ZhangInternational Pharmaceutical Business School of China Pharmaceutical University, Nanjing, 211198, Jiangsu Province, China.
Yong TangThe Taixing People's Hospital, Taixing, 225400, Jiangsu Province, China.
Fang-Zheng DongInternational Pharmaceutical Business School of China Pharmaceutical University, Nanjing, 211198, Jiangsu Province, China.
Ning-Ying MaoInternational Pharmaceutical Business School of China Pharmaceutical University, Nanjing, 211198, Jiangsu Province, China. maoningying@cpu.edu.cn.
Jun LiInternational Pharmaceutical Business School of China Pharmaceutical University, Nanjing, 211198, Jiangsu Province, China. lijun_0607@163.com.

Funding

China Drug Regulatory Affairs Research Association 2025-Y-Y-008
6 · The paper itself

Abstract

backgroundThis study addresses the quality of real-world data (RWD) in oncology and proposes a comprehensive evaluation system for assessing the quality of RWD in the review of anti-tumor drugs. The proposed system provides a solid theoretical foundation and methodological tools to support drug review decisions and offers insights for further enhancing data quality evaluation in regulatory processes.

methodsPreliminary indicators for evaluating the quality of real-world data in anti-tumor drug review were identified based on established domestic and international theories and practices. Expert consultations were conducted to collect feedback from professionals across various fields, further refining the evaluation indicators. The Analytic Hierarchy Process (AHP) was then applied to develop an expert judgment matrix, assigning weights to the indicators according to their relative importance. The final weight values for each indicator were subsequently determined.

resultsThis study developed a real-world data quality evaluation system for anti-tumor drug review, comprising 2 primary indicators, 8 secondary indicators, and 32 tertiary indicators. Weight analysis revealed that data accuracy, source credibility, and population representativeness were the most critical secondary indicators. Among the tertiary indicators, oncology-specific data standards, third-party ethical evaluations, and clarity in inclusion/exclusion criteria and screening processes were identified as the most significant factors. These findings suggest that regulatory agencies should emphasize these aspects more during the quality evaluation process.

conclusionsBased on the key indicators identified in the evaluation system, it is recommended that drug regulatory agencies focus on the following aspects when assessing the quality of real-world data in anti-tumor drug reviews: (1) clear definition of core data elements and critical variables; (2) evaluation of data quality in alignment with research objectives; and (3) ensuring data security and consistency to enhance overall data quality.

Indexed as

Antineoplastic AgentsData AccuracyChinaHumansAntineoplastic AgentsAnti-tumor drug reviewIndicator systemQuality evaluationReal-world data

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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 OpenQuestion graph.