Evidence map›Paper›PMID 42130623›Full record

ArticleFrontiers in oncology2026

External validation and updating of NTCP models for radiation pneumonitis: QUANTEC, Appelt, and a local simplified model.

Zhi Chen, Heng Li, Lan Liang, Ming Fan, Shunping Huang, Peng Xue, Rui Kong, Zhenzhou Yang, Zhengjun Guo

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Article in Frontiers in oncology, 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

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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

9 authors.

Zhi ChenDepartment of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Heng LiDepartment of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Lan LiangDepartment of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Ming FanDepartment of Radiation Oncology, Precision Radiation in Oncology Key Laboratory of Sichuan Province, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Shunping HuangDepartment of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Peng XueLow-Altitude Science and Engineering College, Shandong University, Weihai, China.
Rui KongDepartment of Oncology, the Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zhenzhou YangDepartment of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zhengjun GuoDepartment of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To externally evaluate and update the QUANTEC and Appelt NTCP models for radiation pneumonitis (RP) in lung cancer patients treated with contemporary IMRT and multimodal therapy, and to preliminarily validate a simplified local model in an independent cohort. Methods: We retrospectively analyzed 580 lung cancer patients treated with thoracic IMRT between 2018 and 2023 as the development cohort. The QUANTEC and Appelt models were evaluated and locally updated using a closed testing procedure to determine the least extensive revision required. Clinical and DVH variables were standardized, and smoking status and pulmonary comorbidity were recoded according to published definitions. A final simplified local model (Model D) was developed using BIC-guided multivariable logistic regression with regularization. Performance was assessed by AUC, Brier score, calibration-in-the-large (CITL), calibration slope, Hosmer-Lemeshow test, and decision curve analysis. External validation of Model D was performed in 100 patients from an independent center using fixed coefficients. Results: Both the QUANTEC and Appelt models showed substantial calibration bias in the local cohort, with systematic underestimation of RP risk. Updating improved calibration as expected, with little change in discrimination. Model D, incorporating age, stage, smoking status, tumor location, pulmonary comorbidity, NLR, SII, V30, and MLD, showed the best apparent overall performance in the development cohort (AUC 0.708, Brier 0.215, CITL = 0, slope = 1, Hosmer-Lemeshow P = 0.599). In the external cohort, discrimination and prediction error were similar (AUC 0.718, 95% CI 0.576-0.831; Brier 0.207), although absolute RP risk was overestimated (CITL = -1.043, slope = 1.133, Hosmer-Lemeshow P < 0.001). Conclusions: The original QUANTEC and Appelt models underestimated RP risk in this contemporary IMRT cohort. Updating improved calibration, whereas discrimination changed little. Model D showed better apparent overall performance and preserved ranking ability in an independent external cohort. Calibration drift across centers suggests that simple recalibration may improve absolute risk estimation in new settings. Clinical trial registration: https://www.chictr.org.cn/hvshowproject.html?id=276191&v=1.1, identifier ChiCTR2500102055.

Indexed as

DVHexternal validationlung cancermean lung doseNLRNTCPradiation pneumonitisSII

Identifiers

PMID42130623
PMCPMC13160778

What Socratic holds

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LicenceCC BY
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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.