Establishment of prognostic nomograms for predicting the progression free survival of EGFR‐sensitizing mutation, advanced lung cancer patients treated with EGFR‐TKIs

Abstract

Background There is a lack of clinically available predictive models for patients with epidermal growth factor receptor (EGFR) mutation positive, advanced non–small cell lung cancer (NSCLC) treated with EGFR‐tyrosine kinase inhibitors (TKIs). Methods The clinical data of patients at the Cancer Hospital, Chinese Academy of Medical Sciences between from January 2016 to January 2021 were retrospectively retrieved as training set. The patients from BENEFIT trial were for the validation cohort. The nomogram was built based on independent predictors identified by univariate and multivariate Cox regression analyses. The discrimination and calibration of the nomogram were evaluated by C‐index and calibration plots. Results A total of 502 patients with complete clinical data and follow‐up information were enrolled in this study. Five independent prognostic factors, including The Eastern Cooperative Oncology Group Performance Status scale (ECOG PS), EGFR mutation subtype, EGFR co‐mutation, liver metastasis and malignant pleural effusion (p < 0.05). The C‐indexes of the nomogram were 0.694 (95% confidence interval [CI], 0.663–0.725) for the training set and 0.653 (95% CI, 0.610–0.696) for the validation set. The calibration curves for the probabilities of 9‐, 12‐ and 18‐month progression‐free survival (PFS) revealed satisfactory consistency in both the internal and external validations. Additionally, the patients were divided into two groups according to risk (high‐risk, low‐risk), and significant differences in PFS were observed between the groups in the training and external validation cohorts (p < 0.001). Conclusions We constructed and validated a convenient nomogram that have the potential to become an accurate and reliable tool for patients with EGFR mutation positive, advanced NSCLC to individually predict their potential benefits from EGFR‐TKIs, and facilitate clinical decision‐making.

Clinical outcomes of advanced NSCLC patients with different EGFR exon 19 deletion subtypes treated with first‐line tyrosine kinase inhibitors: A single‐center ambispective cohort study

“…Patients with lung adenocarcinoma harboring EGFR ex19del have generally been considered highly responsive to TKI therapy; however, some patients do not achieve the expected therapeutic response. Based on the differential TKI efficacy observed between EGFR ex19del and L858R mutation, 3,15 researchers have hypothesized that efficacy inconsistencies may also exist among various ex19del subtypes. Among all the identified EGFR ex19del variants, the most common is E746_A750del, accounting for 48.7% to 71.8%, while L747_T751del, L747_P753delinsS, E746_S752delinsV and L747_A750delinsP are among the less common variants, but ranking in the front 9,11,16–18 .…”

“…These mutations are primarily located in the EGFR exon 18–21, which encodes the tyrosine kinase domain, with the exon 19 deletion mutation (ex19del) accounting for 41.2% 2 . Compared with another common sensitive mutation, EGFR exon 21 L858R, ex19del is an independent predictive factor of longer progression‐free survival (PFS) in the first‐line treatment with tyrosine kinase inhibitors (TKIs) targeting EGFR 3 . Network meta‐analysis has revealed that for patients harboring EGFR ex19del, second‐ or third‐generation TKIs undoubtedly have significantly longer PFS than first‐generation TKIs in the first‐line treatment setting 4 .…”

“… 2 Compared with another common sensitive mutation, EGFR exon 21 L858R, ex19del is an independent predictive factor of longer progression‐free survival (PFS) in the first‐line treatment with tyrosine kinase inhibitors (TKIs) targeting EGFR. 3 Network meta‐analysis has revealed that for patients harboring EGFR ex19del, second‐ or third‐generation TKIs undoubtedly have significantly longer PFS than first‐generation TKIs in the first‐line treatment setting. 4 However, the difference between them is not significant, and the improvement in overall survival (OS) is not significant when compared with first‐line chemotherapy containing pemetrexed.…”

Construction of a Nomogram to Predict the Progression Free Survival in Patients With Lung Cancer

“…Ye et al( 29) set a 2-year disease progression nomogram for stage one patients based on tumor size and the maximum standardized uptake value over thirteen parameters, reaching an 81% reliability. Moreover, Du et al (31) established a 9-, 12-, and 18 month PFS nomogram for patients treated in the rst line with EGFR-tyrosine kinase inhibitors (TKIs), based on ve categorical variables, including the ECOG PS, EGFR mutation subtype and EGFR co-mutation, liver metastasis, and malignant pleural effusion, with an approximate AUC of 0.77, which was low comparatively with us, and potentially, the model presents a lack in predicting the outcome with the presence of redundancy information regarding EGFR co-mutation (yes vs no) and EGFR mutation subtype (19del vs 21L858). In another PFS developed model, Liu et al (32) suggest that only in ammatory markers can predict the 6-, 12-, and 18-month PFS.…”

“…Because LC is pathologically heterogeneous in regard to survival outcome, the exploration of survival prediction related to a speci c population is of utmost importance. Despite numerous previously published prognostic models (29)(30)(31)(32)(33), no nomogram has been established for the African population.…”