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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2023

Open Access 01-12-2023 | NSCLC | Article

Stratifying non-small cell lung cancer patients using an inverse of the treatment decision rules: validation using electronic health records with application to an administrative database

Authors: Min-Hyung Kim, Sojung Park, Yu Rang Park, Wonjun Ji, Seul-Gi Kim, Minji Choo, Seung-Sik Hwang, Jae Cheol Lee, Hyeong Ryul Kim, Chang-Min Choi

Published in: BMC Medical Informatics and Decision Making | Issue 1/2023

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Abstract

Background

To validate a stratification method using an inverse of treatment decision rules that can classify non-small cell lung cancer (NSCLC) patients in real-world treatment records.

Methods

(1) To validate the index classifier against the TNM 7th edition, we analyzed electronic health records of NSCLC patients diagnosed from 2011 to 2015 in a tertiary referral hospital in Seoul, Korea. Predictive accuracy, stage-specific sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and c-statistic were measured. (2) To apply the index classifier in an administrative database, we analyzed NSCLC patients in Korean National Health Insurance Database, 2002–2013. Differential survival rates among the classes were examined with the log-rank test, and class-specific survival rates were compared with the reference survival rates.

Results

(1) In the validation study (N = 1375), the overall accuracy was 93.8% (95% CI: 92.5–95.0%). Stage-specific c-statistic was the highest for stage I (0.97, 95% CI: 0.96–0.98) and the lowest for stage III (0.82, 95% CI: 0.77–0.87). (2) In the application study (N = 71,593), the index classifier showed a tendency for differentiating survival probabilities among classes. Compared to the reference TNM survival rates, the index classification under-estimated the survival probability for stages IA, IIIB, and IV, and over-estimated it for stages IIA and IIB.

Conclusion

The inverse of the treatment decision rules has a potential to supplement a routinely collected database with information encoded in the treatment decision rules to classify NSCLC patients. It requires further validation and replication in multiple clinical settings.
Appendix
Available only for authorised users
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Metadata
Title
Stratifying non-small cell lung cancer patients using an inverse of the treatment decision rules: validation using electronic health records with application to an administrative database
Authors
Min-Hyung Kim
Sojung Park
Yu Rang Park
Wonjun Ji
Seul-Gi Kim
Minji Choo
Seung-Sik Hwang
Jae Cheol Lee
Hyeong Ryul Kim
Chang-Min Choi
Publication date
01-12-2023
Publisher
BioMed Central
Keywords
NSCLC
NSCLC
Published in
BMC Medical Informatics and Decision Making / Issue 1/2023
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-022-02088-x

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