Predicting the Mortality Benefit of CT Screening for Second Lung Cancer in a High-Risk Population

Prediction of lung cancer risk based on age and smoking history

BACKGROUND AND OBJECTIVE

The CISNET models provide predictions for dying of lung cancer in any year of life as a function of age and smoking history, but their predictions are quite variable and the models themselves can be complex to implement. Our goal was to develop a simple empirical model of the risk of dying of lung cancer that is mathematically constrained to produce biologically appropriate probability predictions as a function of current age, smoking start age, quit age, and smoking intensity.

METHODS

The six adjustable parameters of the model were evaluated by fitting its predictions of cancer death risk versus age to the mean of published predictions made by the CISNET models for the never smoker and for six different scenarios of lifetime smoking burden.

RESULTS

The mean RMS fitting error of the model was 6.16 × 10 ^-2 (% risk of dying of cancer per year of life) between 55 and 80 years of age. The model predictions increased monotonically with current age, quit age and smoking intensity, and decreased with increasing start age.

CONCLUSIONS

Our simple model of the risk of dying of lung cancer in any given year of life as a function of smoking history is easily implemented and thus may serve as a useful tool in situations where the mortality risks of smoking need to be estimated.

Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC

OBJECTIVES

Several studies have reported that patients operated on for non-small cell lung cancer (NSCLC) are at high risk of second primary lung cancer (SPLC). However, widely varying estimates of this risk have been reported, with very few studies taking into account that these patients are at particularly high competing risk of death, due to recurrence of the initial disease and to comorbidities. Risk factor evaluation over time has significant repercussions on the post-surgery surveillance strategy offered for NSCLC. This study primarily sought to measure the risk of SPLC in a long-term follow-up series, using statistical methods considering competing risks of death.

MATERIALS AND METHODS

The cumulative SPLC risk was estimated using the cumulative incidence of patients with completely resected Stage I-III NSCLC diagnosed between 2002 and 2015 based on the Doubs and Belfort cancer registry (France). A proportional sub-distribution hazard model (_sdRH) was used to investigate factors associated with SPLC risk in the presence of competing risks.

RESULTS

Among the 522 patients, adenocarcinoma and Stage I or II disease accounted for 52.3% and 75.7% of patients, respectively. Overall, 84 patients developed SPLC (16.1%). The cumulative risk of SPLC was 20.2% at 10 years post-surgery (95% confidence interval [CI]: 15.3-23.2), and 25.2% (CI: 19.4-31.3) at 14 years post-surgery. On multivariate analysis, the SPLC risk was significantly higher in patients with postoperative thoracic radiotherapy (_sdRH 2.79; 95% CI: 1.41-5.52; p = 0.003).

CONCLUSION

This study using appropriate statistical methods to consider competing risks showed that after complete NSCLC resection, the cumulative incidence function of SPLC was high, with patients receiving postoperative thoracic radiotherapy at higher risk. These data support the need for life-long follow-up of patients who undergo NSCLC surgery, with the objective of screening for SPLC.