Folate receptor alpha (FRα) is known to be upregulated in a variety of cancers, including non-small cell lung cancer (NSCLC) and breast cancer. To ensure reliable implementation of diagnostic- and therapeutic agents, concordance of FRα expression between biopsy, primary tumor and metastases is important. Using immunohistochemistry (Mab 26B3.F2) these concordances were investigated in 60 NSCLC and 40 breast cancer patients. False positivity of FRα expression on breast and lung cancer biopsies was limited to less than 5%. In NSCLC, FRα expression was shown in 21/34 adenocarcinomas and 4/26 squamous cell carcinomas (SCC). Concordance of FRα expression between biopsy and primary tumor was achieved in respectively 83% and 91% of adenocarcinomas and SCCs. Approximately 80% of all local and distant metastases of NSCLC patients showed concordant FRα expression as their corresponding primary tumor. In breast cancer, FRα positivity was shown in 12/40 biopsies, 20/40 lumpectomies and 6/20 LN metastases, with concordance of 68% between biopsy and primary tumor and 60% between primary tumor and LN metastases. In conclusion, this study shows high concordance rates of FRα expression between biopsies and metastases compared to primary NSCLC and breast cancers, underscoring the applicability of FRα-targeted agents in these patients.

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IntroductionInnovations in head and neck cancer (HNC) treatment are often subject to economic evaluation prior to their reimbursement and subsequent access for patients. Mapping functions facilitate economic evaluation of new treatments when the required utility data is absent, but quality of life data is available. The objective of this study is to develop a mapping function translating the EORTC QLQ-C30 to EQ-5D-derived utilities for HNC through regression modeling, and to explore the added value of disease-specific EORTC QLQ-H&N35 scales to the model.MethodsData was obtained on patients with primary HNC treated with curative intent derived from two hospitals. Model development was conducted in two phases: 1. Predictor selection based on theory- and data-driven methods, resulting in three sets of potential predictors from the quality of life questionnaires; 2. Selection of the best out of four methods: ordinary-least squares, mixed-effects linear, Cox and beta regression, using the first set of predictors from EORTC QLQ-C30 scales with most correspondence to EQ-5D dimensions. Using a stepwise approach, we assessed added values of predictors in the other two sets. Model fit was assessed using Akaike and Bayesian Information Criterion (AIC and BIC) and model performance was evaluated by MAE, RMSE and limits of agreement (LOA).ResultsThe beta regression model showed best model fit, with global health status, physical-, role- and emotional functioning and pain scales as predictors. Adding HNC-specific scales did not improve the model. Model performance was reasonable; R2 = 0.39, MAE = 0.0949, RMSE = 0.1209, 95% LOA of -0.243 to 0.231 (bias -0.01), with an error correlation of 0.32. The estimated shrinkage factor was 0.90.ConclusionsSelected scales from the EORTC QLQ-C30 can be used to estimate utilities for HNC using beta regression. Including EORTC QLQ-H&N35 scales does not improve the mapping function. The mapping model may serve as a tool to enable cost-effectiveness analyses of innovative HNC treatments, for example for reimbursement issues. Further research should assess the robustness and generalizability of the function by validating the model in an external cohort of HNC patients.

Excellent local control rates can be achieved with extensive (local) surgical treatment and postoperative RT. In case of lymph node metastases, a neck dissection with adjuvant postoperative RT is warranted. In patients with node-negative disease, a less aggressive approach for the neck seems feasible to reduce treatment-related morbidity.

Background: This study aims to evaluate the cost-effectiveness of using heat and moisture exchangers (HMEs) vs alternative stoma covers (ASCs) following laryngectomy in the United States. Methods: A cost-effectiveness and budget impact analysis were conducted including uncertainty analyses using real-world survey data with pulmonary events and productivity loss.