Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges

Abstract

Randomised clinical trials have shown the efficacy of computed tomography lung cancer screening, initiating discussions on whether and how to implement population-based screening programs. Due to smoking behaviour being the primary risk-factor for lung cancer and part of the criteria for determining screening eligibility, lung cancer screening is inherently risk-based. In fact, the selection of high-risk individuals has been shown to be essential in implementing lung cancer screening in a cost-effective manner. Furthermore, studies have shown that further risk-stratification may improve screening efficiency, allow personalisation of the screening interval and reduce health disparities. However, implementing risk-based lung cancer screening programs also requires overcoming a number of challenges. There are indications that risk-based approaches can negatively influence the trade-off between individual benefits and harms if not applied thoughtfully. Large-scale implementation of targeted, risk-based screening programs has been limited thus far. Consequently, questions remain on how to efficiently identify and invite high-risk individuals from the general population. Finally, while risk-based approaches may increase screening program efficiency, efficiency should be balanced with the overall impact of the screening program. In this review, we will address the opportunities and challenges in applying risk-stratification in different aspects of lung cancer screening programs, as well as the balance between screening program efficiency and impact.

Keywords: lung cancer screening; personalised screening; risk-based screening.

FIGURE 1

Estimated levels of risk across different lung cancer risk‐prediction models. Examples of estimated absolute 5 (LLPv2 and LLPv3) or 6 (Bach, LCRAT, LCDRAT, PLCOm2012) year risks for four individuals with different risk factors. Person 1: 60‐year‐old high school graduated white male, current smoker, who smoked 25 cigarettes per day for 38 years, has a BMI of 27, has COPD, no asbestos exposure, no personal history of cancer, no personal history of pneumonia and no family history of lung cancer. Person 2: 64‐year‐old college graduated white female, current smoker, who smoked 20 cigarettes per day for 42 years, has a BMI of 26, has no COPD, no asbestos exposure, no personal history of cancer, no personal history of pneumonia and no family history of lung cancer. Person 3: 57‐year old African‐American male with some college education, former smoker who quit 8 years ago, who smoked 15 cigarettes per day for 35 years, has a BMI of 23, has no COPD, has asbestos exposure, no personal history of cancer, a personal history of pneumonia and no family history of lung cancer. Person 4: 68‐year post‐college graduated Hispanic female, former smoker, who quit 12 years ago, smoked 10 cigarettes per day for 33 years, has a BMI of 22, has COPD, no asbestos exposure, no personal history of cancer, no personal history of pneumonia and a family history of lung cancer (one parent, age <60 at diagnosis) [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 2

Estimated lung cancer risk over time by different lung cancer risk‐prediction models. The figure shows the estimated risk over ages 55 through 80 for a hypothetical individual. At each age, the person's 5 (LLPv2 and LLPv3) or 6 (Bach, LCRAT, LCDRAT, PLCOm2012) year risks were estimated. The individual is a high school graduated white male, current smoker, who smoked 15 cigarettes per day since he was 15 years old (40 years of smoking at age 55), has a BMI of 23, no COPD, no asbestos exposure, no personal history of cancer, no personal history of pneumonia and no family history of lung cancer. At age 56 he quits smoking and at age 67 he develops COPD. His BMI is assumed to remain constant over ages 55‐80 [Color figure can be viewed at wileyonlinelibrary.com]