Toward personalized dose-prescription in locally advanced non-small cell lung cancer: Validation of published normal tissue complication probability models

Abstract

Purpose: To identify published normal tissue complication probability (NTCP) models suitable for patient-specific dose-prescription in locally advanced non-small cell lung cancer (LA-NSCLC) through in-house validation.

Material and methods: From eight previously published candidate NTCP models (≥grade 2 acute esophagitis and radiation pneumonitis; AE2, RP2), patient-specific dose-responses were calculated using model variables and fractionation-corrected doses for 241 LA-NSCLC patients treated with chemo-IMRT to 50-80 Gy@1.8-2.0 Gy between 2004 and 2014 (AE2/RP2 rate: 50%/12%). A model was judged final if it significantly predicted AE2 or RP2 (p ≤ 0.05), was discriminative and well calibrated (AUC > 0.60; Hosmer-Lemeshow test p_HL > 0.05), which were assessed as the median over 1000 bootstrap samples.

Results: Models for AE2 had superior discrimination to RP2 models (AUC = 0.63-0.65 vs. 0.51-0.65). The final AE2 model included mean esophageal dose and concurrent chemotherapy (AUC = 0.65; p < 0.0001). The final RP2 model was a slightly adjusted version of the RP2 model with the best discrimination, and included age, mean lung dose, and pulmonary comorbidity (AUC = 0.73; p < 0.0001).

Conclusion: Of the eight investigated and published NTCP models, one model successfully described AE2 and one slightly adjusted model successfully described RP2 in the independent cohort. Estimates from these two NTCP models will, therefore, be considered internally when prescribing patient-specific doses in LA-NSCLC patients.

Keywords: Dose response; Esophagitis; Lung cancer; Pneumonitis; Radiotherapy; Toxicity.

Fig 1.

Dose-response curves for the four published AE2 models (AE2_M1-M4) as applied to the independent cohort. Note: AE2 predictions are given by blue lines; observed AE2 is denoted by black quintiles (error bars: 95% binomial confidence intervals); quintile-specific predicted/observed AE2 rates [%] are given above each quintile; the argument of each model’s logistic-regression based equation is given on the x-axis

Fig 2.

Dose-response curves for the four published RP2 models (RP2_M1-M4) as applied to the independent cohort. Note: For RP2_{M3, M4}, calibration curves are instead given; RP2 predictions are given by orange lines; observed RP2 is denoted by black quintiles (error bars: 95% binomial confidence intervals); quintile-specific predicted/observed RP2 rates [%] are given above each quintile; black dotted lines for RP_M3 and RP_M4 are identity lines; for RP_M1 and RP_M2 the argument of each model’s logistic-regression based equation is given on the x-axis

Fig 3.

Calibration curve for the modified RP2_M4, i.e., RP2 _M4mod based on the prevalence and ORs only for age and pulmonary comorbidity in the independent cohort. Note: RP2 predictions are given by orange lines; observed RP2 is denoted by black quintiles (error bars: 95% binomial confidence intervals); quintile-specific predicted/observed RP2 rates are given above each quintile; the black dotted line is an identity line.