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Background <p>New factors predicting response in patients with a PD-L1 tumor proportion score (TPS) ≥ 50% for locally advanced or metastatic non-small cell lung cancer (NSCLC) are needed to better select first-line therapy. Based on the literature, we previously developed a radiomic model predicting the KEAP1/NFE2L2 mutational status.</p> Method <p>This was a retrospective monocenter study including 94 consecutive patients with advanced or metastatic PD-L1 ≥ 50% NSCLC, treated with pembrolizumab, who underwent a pre-therapeutic FDG-PET/CT and were followed up for 1 year. Seventy-seven patients who did not progress within the first 60 days of treatment were analyzed. Each primary lesion was segmented by 2 physicians on PET and CT scans. Radiomic features were calculated using MIM software on both PET and CT imaging. A previously developed KEAP1/NFE2L2 radiomic prediction model (called MUT<sub>PET</sub>) was applied to this cohort using the initial FDG-PET/CT. The primary endpoint was the validation of the MUT<sub>PET</sub> model as a predictive factor of PFS via the non-invasive prediction of KEAP1/NEF2L2 mutation.</p> Results <p>The main characteristics of this cohort were: median age of 67.0 years [range, 48.0–84.0], sex ratio M/F = 60/17, 74.0% of patients with a histopathology of adenocarcinoma and 85.0% with a stage IV disease. The median follow-up was 20.0 months [range, 15.3–23.9]. Fifty-six (72.2%) patients experienced a disease progression with a median PFS of 11.8 months (CI95% 8.6–15.8) among which 51 (66.2%) died. In univariable analysis, MUT<sub>PET</sub> model was statistically significant as a predictive factor of improved PFS (HR = 0.51, CI95% 0.30–0.91, <i>p</i> = 0.02) whereas it was not statistically significant regarding OS (HR = 0.61, CI95% 0.34–1.11, <i>p</i> = 0.10). In multivariable analysis, the MUT<sub>PET</sub> model was associated with a HR of 0.6 (CI95% 0.34–1.06, <i>p</i> = 0.08). Combining the MUT<sub>PET</sub> prediction, the histology subtype and the existence of liver metastases, a multimodal nomogram was able to predict PFS (chi-test of 39.43, <i>p</i> &lt; 0.0001).</p> Conclusion <p>In PD-L1 TPS ≥ 50% NSCLC patients treated with pembrolizumab, our results suggest an improved PFS in patients predicted to be KEAP1/NFE2L2 mutated.</p>

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Survival impact of a KEAP1-NFE2L2 radiomics model in PDL1 ≥ 50% non-small cell lung cancer treated with pembrolizumab: the PEMBROMIC study

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  • 发表日期：

    2025年11月22日

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  • Coline Le Meur,
  • Karim Amrane,
  • Renaud Descourt,
  • Matthieu Chasseray,
  • Olivier Pradier,
  • David Bourhis,
  • Ronan Abgral,
  • Vincent Bourbonne

摘要

Background

New factors predicting response in patients with a PD-L1 tumor proportion score (TPS) ≥ 50% for locally advanced or metastatic non-small cell lung cancer (NSCLC) are needed to better select first-line therapy. Based on the literature, we previously developed a radiomic model predicting the KEAP1/NFE2L2 mutational status.

Method

This was a retrospective monocenter study including 94 consecutive patients with advanced or metastatic PD-L1 ≥ 50% NSCLC, treated with pembrolizumab, who underwent a pre-therapeutic FDG-PET/CT and were followed up for 1 year. Seventy-seven patients who did not progress within the first 60 days of treatment were analyzed. Each primary lesion was segmented by 2 physicians on PET and CT scans. Radiomic features were calculated using MIM software on both PET and CT imaging. A previously developed KEAP1/NFE2L2 radiomic prediction model (called MUTPET) was applied to this cohort using the initial FDG-PET/CT. The primary endpoint was the validation of the MUTPET model as a predictive factor of PFS via the non-invasive prediction of KEAP1/NEF2L2 mutation.

Results

The main characteristics of this cohort were: median age of 67.0 years [range, 48.0–84.0], sex ratio M/F = 60/17, 74.0% of patients with a histopathology of adenocarcinoma and 85.0% with a stage IV disease. The median follow-up was 20.0 months [range, 15.3–23.9]. Fifty-six (72.2%) patients experienced a disease progression with a median PFS of 11.8 months (CI95% 8.6–15.8) among which 51 (66.2%) died. In univariable analysis, MUTPET model was statistically significant as a predictive factor of improved PFS (HR = 0.51, CI95% 0.30–0.91, p = 0.02) whereas it was not statistically significant regarding OS (HR = 0.61, CI95% 0.34–1.11, p = 0.10). In multivariable analysis, the MUTPET model was associated with a HR of 0.6 (CI95% 0.34–1.06, p = 0.08). Combining the MUTPET prediction, the histology subtype and the existence of liver metastases, a multimodal nomogram was able to predict PFS (chi-test of 39.43, p < 0.0001).

Conclusion

In PD-L1 TPS ≥ 50% NSCLC patients treated with pembrolizumab, our results suggest an improved PFS in patients predicted to be KEAP1/NFE2L2 mutated.