Incorporation of EGFR mutation status into M descriptor of new TNM classification influences survival curves in non-small cell lung cancer patients

To establish a prognostic model of epidermal growth factor receptor mutated non-small cell lung cancer patients based on Least Absolute Shrinkage and Selection Operator regression

BACKGROUND

There is currently a shortage of effective diagnostic tools that are used for identifying long-term survival among non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations. This research utilized the development of a prognostic model to assist clinicians in forecasting the survival over 24 months.

METHODS

In Phase III and IV those patients who were diagnosed with EGFR mutation from January 2018 to June 2022 were enrolled into the lung cancer group of Thoracic Surgery Department of Hebei Provincial People's Hospital. Long-run survival was stated as survival for 24 months after being diagnosed. A multivariate prognostic pattern was constructed by means of internal validation and binary logistic regression by bootstrapping. One nomogram was created with a view to boosting the explanation and applicability of the pattern.

RESULTS

A total of 603 patients with EGFR mutation were registered. Elements linked to the whole survival beyond 24 months were age (OR 6.15); female (OR 1.79); functional status (ECOG 0-1) (OR 5.26); Exon 20 insertion mutation deletion (OR 2.08); No central nervous system metastasis (OR 2.66), targeted therapy (OR 0.43); Immunotherapy (OR 0.24). The model has good internal validation.

CONCLUSION

Seven pretreatment clinicopathological variables predicted survival over 24 months. That pattern owns a great discriminative capability. It is hypothesized that this pattern is capable of assisting in selecting the optimal treatment sequence for NSCLC patients with EGFR mutations.

Human Papillomavirus Is Associated With Adenocarcinoma of Lung: A Population-Based Cohort Study

Background

Recent trends in the incidence of lung cancer have been reported despite the decreasing rate of smoking. Lung cancer is ranked among the top causes of cancer-related deaths. The ratio of adenocarcinoma to squamous cell carcinoma, as well as the ratio of women to men, is still increasing. Human papillomavirus (HPV) has been discovered in lung cancer tissues and blood specimens, particularly in Eastern countries. However, the association between HPV infection and lung adenocarcinoma remains unclear.

Methods

This population-based cohort study was conducted using data from Taiwan's single-payer national health insurance and cancer registry databases. Data on HPV infection, cancer, sex, age, comorbidities, urbanization, and occupation were collected. The cumulative incidence rates were generated using Kaplan–Meier curves and log-rank tests. COX regression analysis was used to estimate the hazard ratios of factors associated with cancer occurrence. We used data from 2007 and 2015. The cases were matched with sex and age in a 1:2 manner with 939,874 HPV+ and 1,879,748 HPV– individuals, respectively.

Results

The adjusted hazard ratios [95% confidence interval (CI)] for HPV infection in all lung cancers were 1.539 (1.436–1.649), male lung cancer 1.434 (1.312–1.566), female lung cancer 1.742 (1.557–1.948), squamous cell carcinoma (SCC) 1.092 (0.903–1.320), male SCC 1.092 (0.903–1.320), female SCC 0.949 (0.773–1.164), adenocarcinoma 1.714 (1.572–1.870), male adenocarcinoma 1.646 (1.458–1.858), and female adenocarcinoma 1.646 (1.458–1.858). The highest adjusted hazard ratio for lung cancer was chronic obstructive pulmonary disease (COPD) 1.799 (1.613–2.007), followed by male sex 1.567 (1.451–6.863) and HPV infection. The highest adjusted hazard ratio for adenocarcinoma was HPV infection 1.714 (1.572–1.870), followed by COPD 1.300 (1.102–1.533), and for SCC, male sex 5.645 (4.43–3.37), followed by COPD 2.528 (2.002–3.192).

Conclusion

Our study showed that HPV infection was associated with the occurrence of adenocarcinoma of the lung in both men and women but was not associated with SCC of the lung.

Effect of epidermal growth factor receptor gene mutation on the prognosis of pathological stage II-IIIA (8th edition TNM classification) primary lung cancer after curative surgery

OBJECTIVES

This retrospective study aimed to elucidate the effect of epidermal growth factor receptor (EGFR) gene mutations on the prognosis of patients with pathological stage II-IIIA primary lung cancer after curative surgery.

MATERIALS AND METHODS

We enrolled 539 patients with p-stage II-IIIA (8th edition tumor-node-metastasis [TNM] classification) lung cancer who underwent curative resection at Kanagawa Cancer Center between January 2010 and December 2020 and whose tumors were tested for EGFR mutations. Relapse-free survival (RFS) and overall survival (OS) of patients with EGFR-mutant lung cancer (Mt, n = 126) including EGFR exon 21 L858R point mutation and EGFR exon 19 deletion mutation and EGFR mutation-wild lung cancer (Wt, n = 413) were analyzed using Kaplan-Meier curves and compared using a log-rank test. Cox regression analysis was performed to evaluate the effects of EGFR gene mutations on RFS and OS at each stage.

RESULTS

There were 56/256 patients with p-stage II EGFR-Mt/Wt and 70/157 patients with p-stage IIIA EGFR-Mt/Wt. The 5-year RFS rate of patients with EGFR-Mt/Wt was 46.6%/52.0% (p = 0.787) for p-stage II and 17.4%/29.7% (p = 0.929) for p-stage IIIA. The 5-year OS rate was 92.0%/65.7% (p = 0.001) for p-stage II and 56.0%/39.3% (p = 0.016) for p-stage IIIA. EGFR-Mt was not an independent prognostic factor for OS of patients with p-stage IIIA lung cancer (hazard ratio [HR], 0.95; 95% confidence interval [CI], 0.51-1.76; p = 0.872); however, EGFR-Mt was an independent favorable prognostic factor for OS of patients with p-stage II lung cancer (HR, 0.59; 95% CI, 0.36-0.96; p = 0.034).

CONCLUSION

The OS of lung cancer patients with p-stage II or IIIA, classified according to the 8th edition TNM classification, was remarkably favorable. Incorporating EGFR mutations to the anatomical TNM classification may lead to a more accurate prognosis prediction.

Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data

BACKGROUND

There is a lack of useful diagnostic tools to identify EGFR mutated NSCLC patients with long-term survival. This study develops a prognostic model using real world data to assist clinicians to predict survival beyond 24 months.

METHODS

EGFR mutated stage IIIB and IV NSCLC patients diagnosed between January 2009 and December 2017 included in the Spanish Lung Cancer Group (SLCG) thoracic tumor registry. Long-term survival was defined as being alive 24 months after diagnosis. A multivariable prognostic model was carried out using binary logistic regression and internal validation through bootstrapping. A nomogram was developed to facilitate the interpretation and applicability of the model.

RESULTS

505 of the 961 EGFR mutated patients identified in the registry were included, with a median survival of 27.73 months. Factors associated with overall survival longer than 24 months were: being a woman (OR 1.78); absence of the exon 20 insertion mutation (OR 2.77); functional status (ECOG 0-1) (OR 4.92); absence of central nervous system metastases (OR 2.22), absence of liver metastases (OR 1.90) or adrenal involvement (OR 2.35) and low number of metastatic sites (OR 1.22). The model had a good internal validation with a calibration slope equal to 0.781 and discrimination (optimism corrected C-index 0.680).

CONCLUSIONS

Survival greater than 24 months can be predicted from six pre-treatment clinicopathological variables. The model has a good discrimination ability. We hypothesized that this model could help the selection of the best treatment sequence in EGFR mutation NSCLC patients.