Predicting long-term absolute risk of lung cancer in Hodgkin lymphoma patients.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: median MLD of 15
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
The 20- and 30-year IPCW AUCs were 0.79 (95% Confidence interval (CI): 0.73-0.85) and 0.75 (95% CI: 0.69-0.81), respectively. [CONCLUSION] We developed a well-calibrated prediction tool that estimates long-term risk of LC with good discrimination based on patient characteristics and MLD, allowing application in HL survivors and contemporary HL patients.
[BACKGROUND] Hodgkin lymphoma (HL) patients are at increased risk of developing lung cancer (LC), especially after chest radiotherapy (RT).
- 95% CI 0.69-0.81
APA
Roshani S, Boekel NB, et al. (2026). Predicting long-term absolute risk of lung cancer in Hodgkin lymphoma patients.. Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djag090
MLA
Roshani S, et al.. "Predicting long-term absolute risk of lung cancer in Hodgkin lymphoma patients.." Journal of the National Cancer Institute, 2026.
PMID
41942100 ↗
Abstract 한글 요약
[BACKGROUND] Hodgkin lymphoma (HL) patients are at increased risk of developing lung cancer (LC), especially after chest radiotherapy (RT). However, there are no tools to predict LC risk for different HL treatments.
[METHODS] In a cohort of 5,370 ≥ 5-year HL survivors aged 15 to 50 years at HL diagnosis and treated in the Netherlands between 1965 to 2012, we used RT fields and prescribed dose to estimate mean lung dose (MLD). The twinning method was used to divide the cohort into homogenous parts: 80% for model development and 20% for validation using Inverse Probability of Censoring Weighting (IPCW) Area Under the Curve (AUC). Cox proportional hazards models allowing for time-dependent coefficient(s) were used to model time from HL diagnosis to LC and LC-free death as competing event for predicting absolute LC risk up to 30 years after HL diagnosis.
[RESULTS] Treatment information was composed of supra-diaphragmatic RT in 75.2% of patients with median MLD of 15.8 Gray. During follow-up, 218 survivors developed LC. Older age, male gender, smoking at HL diagnosis and higher MLD were associated with higher LC risk. The median estimated 30-year absolute LC risk in our cohort was 1.2% (Interquartile range (IQR): 0.8%-1.9%) in non-smokers and 6.9% (IQR: 4.6%-10.9%) in smokers at HL diagnosis. The 20- and 30-year IPCW AUCs were 0.79 (95% Confidence interval (CI): 0.73-0.85) and 0.75 (95% CI: 0.69-0.81), respectively.
[CONCLUSION] We developed a well-calibrated prediction tool that estimates long-term risk of LC with good discrimination based on patient characteristics and MLD, allowing application in HL survivors and contemporary HL patients.
[METHODS] In a cohort of 5,370 ≥ 5-year HL survivors aged 15 to 50 years at HL diagnosis and treated in the Netherlands between 1965 to 2012, we used RT fields and prescribed dose to estimate mean lung dose (MLD). The twinning method was used to divide the cohort into homogenous parts: 80% for model development and 20% for validation using Inverse Probability of Censoring Weighting (IPCW) Area Under the Curve (AUC). Cox proportional hazards models allowing for time-dependent coefficient(s) were used to model time from HL diagnosis to LC and LC-free death as competing event for predicting absolute LC risk up to 30 years after HL diagnosis.
[RESULTS] Treatment information was composed of supra-diaphragmatic RT in 75.2% of patients with median MLD of 15.8 Gray. During follow-up, 218 survivors developed LC. Older age, male gender, smoking at HL diagnosis and higher MLD were associated with higher LC risk. The median estimated 30-year absolute LC risk in our cohort was 1.2% (Interquartile range (IQR): 0.8%-1.9%) in non-smokers and 6.9% (IQR: 4.6%-10.9%) in smokers at HL diagnosis. The 20- and 30-year IPCW AUCs were 0.79 (95% Confidence interval (CI): 0.73-0.85) and 0.75 (95% CI: 0.69-0.81), respectively.
[CONCLUSION] We developed a well-calibrated prediction tool that estimates long-term risk of LC with good discrimination based on patient characteristics and MLD, allowing application in HL survivors and contemporary HL patients.