https://orcid.org/0000-0002-9753-2008
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Abstract
Introduction
Recurrence of cancer is not routinely registered in Danish national health registers. This study aimed to develop and validate a register-based algorithm to identify patients diagnosed with recurrent lung cancer and to estimate the accuracy of the identified diagnosis date.
Material and Methods
Patients with early-stage lung cancer treated with surgery were included in the study. Recurrence indicators were diagnosis and procedure codes recorded in the Danish National Patient Register and pathology results recorded in the Danish National Pathology Register. Information from CT scans and medical records served as the gold standard to assess the accuracy of the algorithm.
Results
The final population consisted of 217 patients; 72 (33%) had recurrence according to the gold standard. The median follow-up time since primary lung cancer diagnosis was 29 months (interquartile interval: 18–46). The algorithm for identifying a recurrence reached a sensitivity of 83.3% (95% CI: 72.7–91.1), a specificity of 93.8% (95% CI: 88.5–97.1), and a positive predictive value of 87.0% (95% CI: 76.7–93.9). The algorithm identified 70% of the recurrences within 60 days of the recurrence date registered by the gold standard method. The positive predictive value of the algorithm decreased to 70% when the algorithm was simulated in a population with a recurrence rate of 15%.
Conclusion
The proposed algorithm demonstrated good performance in a population with 33% recurrences over a median of 29 months. It can be used to identify patients diagnosed with recurrent lung cancer, and it may be a valuable tool for future research in this field. However, a lower positive predictive value is seen when applying the algorithm in populations with low recurrence rates.
Abbreviations
CCC, concordance correlation coefficient; CI, confidence interval; ICD-10, International Classification of Diseases, 10th revision; NPV, negative predictive value; PPV, positive predictive value; SCLC, small-cell lung cancer; SNOMED, Systematized Nomenclature of Medicine; UICC, Union for International Cancer Control.
Data Sharing Statement
The data supporting the findings of this study is stored and maintained electronically on servers at Statistics Denmark. The data is only accessible through a secure virtual private network (VPN) and only for pre-approved collaborative partners. The data is not publicly available due to the Danish data protection legislation as the data contains information that could compromise the privacy of the research participants.
Ethical Approval
The project is approved and registered as “The patient pathway for cancer recurrence” (study 1, id 119) in the Record of Processing Activities at the Research Unit for General Practice in Aarhus in accordance with the provisions of the General Data Protection Regulation (GDPR). According to the Danish committee law, §14, 2, the study required no approval from the Committee on Health Research Ethics of the Central Denmark Region as “no biomedical intervention was performed”.Citation33
Author Contributions
LAR, LFV, HJ, and PV conceived the concept of the study. AWL, NLC, and SOD provided data on the gold standards. LAR was responsible for the data acquisition, data management, statistical analyses and drafted the manuscript. All authors contributed with significant contribution to the reported work, including the analyses, interpretation of data and substantial and critical review of the article. All authors read and approved the final version of the manuscript and agreed on the submission to Clinical Epidemiology. All authors agree to take responsibility and be accountable for the contents of the article.
Disclosure
The authors declare that they have no conflicts of interest in this work.