The epidemiological and demographic data for the validation set of 1066 LC patients and 677 controls are presented in . Patients (mean age, 64.8 years) were older than controls (mean age, 61.1 years; P
<0.001). The majority of patients (58%) and controls (52%) were male. There was a higher percentage of former smokers among controls (74.2%) than among patients (56.2% P
<0.001). Lung cancer patients who were current smokers smoked significantly more cigarettes per day (mean, 29.9), and had smoked for longer periods (mean, 43.8 years) than did controls (mean cigarettes smoked per day: 21.1, P
<0.001; smoking duration: 38.5 years, P
<0.001). Similarly, patients who were former smokers had smoked significantly more cigarettes per day (mean, 30.6) and had smoked for longer periods (mean, 34.8 years) than did controls (mean cigarettes smoked per day: 22.9, P
<0.001; smoking duration: 24.2 years, P
<0.001). Lung cancer patient pack-years were over 24
units higher in both current and former smokers than in controls, and these differences were highly significant in both smoking groups (P
<0.001). Controls reported longer quitting durations (mean, 19.8 years) than did patients (mean, 14.1 years; P
<0.001). Former smokers more after reported a family history of any cancer (34.4%) and smoking-related cancers (30.6%) than did controls (any cancer: 27.9%, P
=0.023; smoking-related cancers: 22.9%, P
=0.005); and current smokers reported a significantly higher percentage of smoking-related cancers (30.4%) than did controls (22.3%, P
Demographic characteristics of study population used to compare discriminatory power and accuracy of the Spitz, Bach, and LLP risk models
The discriminatory power for the three models, overall and stratified by smoking, age, and sex, are summarised in , the AUCs being 0.69 for the Spitz (95% CI=0.66–0.71) and LLP (95% CI=0.67–0.71) models and 0.66 (95% CI=0.64–0.69) for the Bach model. The differences in discriminatory power between the LLP and Bach models were significant (P=0.023), and the differences between the Spitz and Bach models reached borderline significance (P=0.072). Among former smokers, the discriminatory power was 0.70 (95% CI=0.67–0.73) for the Spitz and LLP models and 0.65 (95% CI=0.62–0.68) for the Bach model. Among current smokers, the discriminatory power was 0.68 (95% CI=0.64–0.72) for the Spitz model, 0.65 (95% CI=0.60–0.69) for the Bach model, and 0.66 (95% CI=0.62–0.70) for the LLP model. Among former smokers, the Bach model was outperformed by both the LLP (P=0.002) and the Spitz (P=0.008) models, whereas among current smokers, only the Spitz model significantly outperformed the Bach model (P=0.024). When incorporating never smokers for testing discriminatory power, the LLP model (AUC=0.72, 95% CI=0.70–0.74) outperformed the Spitz model (AUC=0.68, 95% CI=0.66–0.71) significantly (P=0.001).
Discriminatory power for the Spitz, Bach, and LLP risk models, overall and stratified by smoking, age, and sex
We also tested the discriminatory power of all models when participants were stratified by age and sex () and for women over the age of 50 years, observed significant differences in discriminatory power between the Spitz and Bach models, and the LLP and Bach models.
summarises the NPV and PPV results for each. Overall, the three models had reasonable PPV levels (all >70%); the Spitz model had a significantly higher PPV (88.2%) than those of the LLP (75.9% P<0.001) and the Bach (80.9% P=0.009) models. Among former smokers, the Spitz model had significantly higher PPV (85.5%) than did the LLP model (72.6% P<0.001) but not significantly higher PPV than the Bach model (83.6% P=0.851). However, among current smokers, the Spitz model had higher PPV (91.9%) than did the Bach (80.4% P=0.002) and the LLP (80.9% P<0.001) models. The overall NPV for each of the three models were lower than the PPV (range=45.0–56.0%), with the LLP model having a substantially better probability of accurately categorising an unaffected participant. The LLP model was also significantly better for the NPV among former smokers, but both the Spitz and Bach models were competitive with the LLP model in calculating the NPV among current smokers.
Positive predictive and negative predictive values (PPV and NPV, respectively) examination using a predictive cutoff of 2.5%
To demonstrate the clinical utility of each model, presents the percentages of patients and controls with LC risk estimates of >2.5, 5, and 7.5% as determined by each model. Using a cutoff of >2.5% risk as an example, the percentages of LC patients that were correctly identified by the Spitz, Bach, and LLP risk models were 26.6, 30.2, and 66.7%, respectively. The percentages of controls with >2.5% risk that were incorrectly identified as LC patients by the Spitz, Bach, and LLP risk models were 5.6, 11.2, and 33.4%, respectively. For all three models, setting a higher risk cutoff resulted in a lower proportion of controls being incorrectly identified as LC patients and a lower proportion of LC patients being correctly identified. This is evident in the scaled rectangle diagrams for the Spitz, Bach, and LLP risk models at cutoffs of >2.5, 5, and 7.5% absolute risk, respectively (). Using the >2.5% risk cutoff, the LLP model identified 276 LC patients who were not identified by the Spitz and Bach models, but it also incorrectly identified 139 controls as LC patients. Although the Spitz and Bach models identified fewer LC patients (17 and 15, respectively), significantly fewer controls were incorrectly identified as patients (5 and 8, respectively) compared with the LLP model. Using the >7.5% risk cutoff, the Spitz model had 100% specificity, but its sensitivity was impractically low (2.2%). At this level of risk, for every four LC patients correctly identified by the LLP model, one control was incorrectly identified as a LC patient, wherein as the equivalent patient-to-control ratio for the Bach model was 5 to 1.
Clinical utility of the Spitz, Bach, and LLP risk models estimated as percentage of participants with risk estimates >2.5, 5.0, and 7.5%
Figure 1 Clinical utility of the Spitz, Bach, and LLP models. Scaled rectangle diagrams for (A) the Spitz, (B) Bach, and (C) LLP risk models at defined levels of lung cancer risk. For each colour of the diagram: white equals all controls with <2.5% (more ...)