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Purpose: DNA methylation is associated with bladder cancer and these modifications could serve as useful biomarkers. FGFR3 mutations are present in 60% to 70% of non-muscle invasive bladder cancer (NMIBC). Low-grade bladder cancer recurs in more than 50% of patients. The aim of this study is to determine the sensitivity and specificity of a urine assay for the diagnosis of recurrences in patients with a previous primary NMIBC G1/G2 by using cystoscopy as the reference standard.Experimental Design: We selected eight CpG islands (CGI) methylated in bladder cancer from our earlier genome-wide study. Sensitivity of the CGIs for recurrences detection was investigated on a test set of 101 preTUR urines. Specificity was determined on 70 urines from healthy males aged more than 50 years. A 3-plex assay for the best combination was developed and validated on an independent set of 95 preTUR, recurrence free, and nonmalignant urines (n ¼ 130).Results: The 3-plex assay identified recurrent bladder cancer in voided urine with a sensitivity of 74% in the validation set. In combination with the FGFR3 mutation assay, a sensitivity of 79% was reached (specificity of 77%). Sensitivity of FGFR3 and cytology was 52% and 57%, respectively.Conclusion: The combination of methylation and FGFR3 assays efficiently detects recurrent bladder cancer without the need for stratification of patients regarding methylation/mutation status of the primary tumor. We conclude that the sensitivity of this combination is in the same range as cystoscopy and paves the way for a subsequent study that investigates a modified surveillance protocol consisting of the urine test followed by cystoscopy only when the urine test is positive.

PRO scores were associated with age, time since surgery, type of surgery, and radiation therapy in breast cancer patients. The scores serve as a reference value for different types of surgery in the study population and enable prospective use of PROs in shared decision-making.

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MEI is an important prognostic factor for mortality in TBI patients. However, the effect varies by population, which explains the controversy in the literature. The strength of the effect is smaller in patients with more severe brain injury and depends on time of inclusion in a study.

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Background Disclosing prognostic information is necessary to enable patients to make well‐informed treatment decisions. OncologIQ is a prognostic model that predicts the overall survival (OS) probability in patients with head and neck squamous cell carcinoma (HNSCC). We aimed to externally validate and update the model with new prognostic factors and translate it to a clinically useful tool. Methods A consecutive retrospective sample of 2189 patients eligible for curative treatment of a primary HNSCC were selected. Discriminative performance was determined using the C‐statistic. Results External validation showed systematic underestimation of OS in the new population, and reasonable discrimination (C‐statistic 0.67). Adding smoking, pack years, BMI, weight loss, WHO performance, socioeconomic status, and p16 positivity to the recalibrated multivariable model, improved the internally validated C‐statistic to 0.71. The model showed minor optimism and was translated in an online tool ( www.oncologiq.nl ). Conclusions The updated model enables personalized patient counseling during treatment decision consultations.