Socio-demographic inequalities in stage at diagnosis of lung cancer: A French population-based study.

BACKGROUND: Diagnosing patients at a non-advanced stage has become a mainstay of lung cancer prevention and control strategies. Understanding socio-demographic inequalities in stage at diagnosis may improve the targeting of interventions on patients at higher risk. This study aimed to identify these socio-demographic determinants in a large-scale French population-based cancer registry. METHODS: All incident lung cancers diagnosed between 2008 and 2019 identified from the Poitou-Charentes Cancer Registry (south-west France) were included. Stage at diagnosis was categorised as advanced/non-advanced (TNM III/IV vs I/II) according to the 8th TNM edition, the objective being to ensure a consistent level of prognosis over time. Socio-demographic variables included age, sex, the French European Deprivation Index (EDI) and patient's place of residence. Their impact on stage at diagnosis was quantified by multivariate logistic regression models with subgroup analyses by histological subtype. RESULTS: Out of the 15,487 included patients, 75% were diagnosed at an advanced stage (66% to 95% depending on the histological subtype), 17% at a non-advanced stage and 10% at a non-specified stage. Multivariate analysis showed different patterns according to histological subtypes. In patients with adenocarcinoma, a higher risk of advanced stage was found for younger and older patients (u-shape), those most deprived, and those living in rural areas. The same effect of age was reported for squamous cell carcinomas, while no association was found for small-cell lung carcinomas. CONCLUSIONS: This study highlighted substantial socio-demographic inequalities in stage at diagnosis, specifically for adenocarcinoma patients. Diagnosis strategies could be refined and strengthened in the non-smoker population, in which adenocarcinomas are mainly reported.

Low RNA disruption during neoadjuvant chemotherapy predicts pathologic complete response absence in patients with breast cancer.

In previously reported retrospective studies, high tumor RNA disruption during neoadjuvant chemotherapy predicted for post-treatment pathologic complete response (pCR) and improved disease-free survival at definitive surgery for primary early breast cancer. The BREVITY (Breast Cancer Response Evaluation for Individualized Therapy) prospective clinical trial (NCT03524430) seeks to validate these prior findings. Here we report training set (Phase I) findings, including determination of RNA disruption index (RDI) cut points for outcome prediction in the subsequent validation set (Phase II; 454 patients). In 80 patients of the training set, maximum tumor RDI values for biopsies obtained during neoadjuvant chemotherapy were significantly higher in pCR responders than in patients without pCR post-treatment (P = .008). Moreover, maximum tumor RDI values ≤3.7 during treatment predicted for a lack of pCR at surgery (negative predictive value = 93.3%). These findings support the prospect that on-treatment tumor RNA disruption assessments may effectively predict post-surgery outcome, possibly permitting treatment optimization.