Predicting Lung Cancer Occurrence in Never-Smoking Females in Asia: TNSF-SQ, a Prediction Model

Abstract

Background: High disease burden suggests the desirability to identify high-risk Asian never-smoking females (NSF) who may benefit from low-dose CT (LDCT) screening. In North America, one is eligible for LDCT screening if one satisfies the U.S. Preventive Services Task Force (USPSTF) criteria or has model-estimated 6-year risk greater than 0.0151. According to two U.S. reports, only 36.6% female patients with lung cancer met the USPSTF criteria, while 38% of the ever-smokers ages 55 to 74 years met the USPSTF criteria. Methods: Using data on NSFs in the Taiwan Genetic Epidemiology Study of Lung Adenocarcinoma and the Taiwan Biobank before August 2016, we formed an age-matched case-control study consisting of 1,748 patients with lung cancer and 6,535 controls. Using these and an estimated age-specific lung cancer 6-year incidence rate among Taiwanese NSFs, we developed the Taiwanese NSF Lung Cancer Risk Models using genetic information and simplified questionnaire (TNSF-SQ). Performance evaluation was based on the newer independent datasets: Taiwan Lung Cancer Pharmacogenomics Study (LCPG) and Taiwan Biobank data after August 2016 (TWB2). Results: The AUC based on the NSFs ages 55 to 70 years in LCPG and TWB2 was 0.714 [95% confidence intervals (CI), 0.660-0.768]. For women in TWB2 ages 55 to 70 years, 3.94% (95% CI, 2.95-5.13) had risk higher than 0.0151. For women in LCPG ages 55 to 74 years, 27.03% (95% CI, 19.04-36.28) had risk higher than 0.0151. Conclusions: TNSF-SQ demonstrated good discriminative power. The ability to identify 27.03% of high-risk Asian NSFs ages 55 to 74 years deserves attention. Impact: TNSF-SQ seems potentially useful in selecting Asian NSFs for LDCT screening.

Development of risk prediction models for lung cancer based on tumor markers and radiological signs

“…Some biomarkers, such as CA125, CA153, HE4, and CA242, metalloproteinase-9 (MMP-9) have been used in other studies. [34][35][36] But these factors have low specificities for diagnosing lung cancer and were usually used to screen female malignancies. Besides, with the development of genomics, proteomics, radiomics, and liquid biopsy techniques, increasing indicators help in predicting the risk of lung cancer in a better way.…”

Associations between female lung cancer risk and sex steroid hormones: a systematic review and meta-analysis of the worldwide epidemiological evidence on endogenous and exogenous sex steroid hormones

“…Lung cancer is the leading cause of cancer-related mortality worldwide, accounting for 22% of all cancer deaths [ 1 , 2 ]. Prevention of lung cancer based on tobacco control has been widely implemented worldwide; however, approximately 25% of lung cancer cases worldwide still occur in never-smokers, especially in women [ 3 – 8 ]. Notably, many more lung cancer cases occur in Asian never-smokers than in Western never-smokers [ 4 , 9 ].…”

Current lung cancer screening guidelines may miss high-risk population: a real-world study

“…In addition, the epidemiological differences in lung cancer incidence and risk factors between Chinese and US populations suggest that inclusion of ambient air pollution exposure and gender into lung cancer risk prognostic models might better capture high-risk individuals, especially for non-smoking women [ 45 ]. Recently, a predicting lung cancer occurrence in never-smoking Asian females has been proposed [ 46 ].…”

“…In addition, the epidemiological differences in lung cancer incidence and risk factors between Chinese and US populations suggest that inclusion of ambient air pollution exposure and gender into lung cancer risk prognostic models might better capture high-risk individuals, especially for non-smoking women [45]. Recently, a predicting lung cancer occurrence in never-smoking Asian females has been proposed [46]. a The screenings were performed at 1-year intervals, with the first screening (T0) performed soon after the time of randomization On the other hand, of all lung cancers detected in our study, 28.1% patients were younger than years, and 10.6% patients were older than 80 years.…”