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Including tumor-infiltrating lymphocytes into the PREDICT prognostic model for triple-negative breast cancer survival

  • Y Wang
  • , D Drubay
  • , S F Jonas
  • , J Dixon-Douglas
  • , B Acs
  • , S Adams
  • , F André
  • , S Badve
  • , G Bataillon
  • , J M Carter
  • , S Chia
  • , V Cockenpot
  • , M A Colleoni
  • , C Criscitiello
  • , G Curigliano
  • , G M H E Dackus
  • , S Demaria
  • , C Denkert
  • , C H M van Deurzen
  • , M V Dieci
  • D Giardiello, M P Goetz, R J Gray, M Hauptmann, N D Ter Hoeve, K Jóźwiak, E A Koop, V M T de Jong, H Joensuu, G Jules-Clément, R Kammler, P L Kellokumpu-Lehtinen, S B Kim, M Kok, M Lacroix-Triki, M Lambertini, H J Lee, J Lemonnier, R A Leon-Ferre, S Leung, B Linderholm, S Loibl, J W M Martens, T O Nielsen, M Opdam, P Pharoah, F Penault-Llorca, P J van Diest, S C Linn, M K Schmidt*,
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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. 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%. 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. 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.

Original languageEnglish
Pages (from-to)1093-1105
Number of pages13
JournalAnnals of Oncology
Volume37
Issue number8
Early online date21 Apr 2026
DOIs
Publication statusPublished - Aug 2026

Keywords

  • PREDICT
  • chemotherapy-decision making
  • prognostication
  • triple-negative breast cancer
  • tumor-infiltrating lymphocytes

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