Abstract
PATIENTS AND METHODS
We included 3698 women with early-stage TNBC, diagnosed between 1979 and 2017, from two pooled cohorts with sTILs scored according to international guidelines to update PREDICT version 2.3. The updated model, PREDICT_sTILs, is a Cox regression model with sTILs and the PREDICT prognostic index as predictors and breast cancer-specific survival as the outcome. Internal-external validation was conducted using leave-one-region-out cross-validation, with calibration assessed by the observed-to-expected (O/E) ratio and discrimination by area under the curve (AUC). We compared the clinical values of PREDICT_sTILs and PREDICT through decision curve analysis, examining net true high-risk and low-risk classifications across risk thresholds of 10-year breast cancer mortality above 8%-15%.
CONCLUSION
Adding sTILs to PREDICT improves its ability to inform chemotherapy decisions for early-stage patients with TNBC, especially in identifying low-risk individuals who may safely forgo chemotherapy.
RESULTS
Among the 3698 patients, 1806 received chemotherapy while 1892 were chemotherapy-naïve. Chemotherapy-treated patients had a median age of 50 years, a tumor size of 25 mm, and one positive lymph node. The chemotherapy-naïve patients had a median age of 55 years, a tumor size of 20 mm, and 0 positive lymph nodes. Within 5 and 10 years, 741 and 860 deaths were attributed to breast cancer, respectively. PREDICT_sTILs showed strong internal-external validity, with comparable calibration and discrimination at both time points: pooled O/E ratios of 0.98 [95% confidence interval (CI) 0.69-1.41] at 5 years and 0.99 (95% CI 0.72-1.35) at 10 years, and AUCs of 0.74 (95% CI 0.72-0.77) and 0.74 (95% CI 0.70-0.78), respectively. Compared with PREDICT, PREDICT_sTILs identified 19-60 additional net true low-risk patients and 3-10 additional net true high-risk patients per 1000 chemotherapy-naïve patients at the risk thresholds of 8%-15% at 10 years.
BACKGROUND
Stromal tumor-infiltrating lymphocytes (sTILs) are a strong prognostic marker in patients with triple-negative breast cancer (TNBC). We aimed to incorporate sTILs into the PREDICT model for women with early-stage TNBC to guide chemotherapy decisions.