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Focuses on drug treatment of hypertension in the elderly. Role of alpha-adrenoceptor blockade; Level of blood pressure lowering in the elderly needed; Treatment of patients with isolated systolic hypertension.

Abstract Background The intensive care unit (ICU) length of stay (LOS) of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP), a machine learning technique. Methods Non-interventional study. Predictive modeling, separate development (n = 461) and validation (n = 499) cohort. GP models were developed to predict the probability of ICU discharge the day after surgery (classification task), and to predict the day of ICU discharge as a discrete variable (regression task). GP predictions were compared with predictions by EuroSCORE, nurses and physicians. The classification task was evaluated using aROC for discrimination, and Brier Score, Brier Score Scaled, and Hosmer-Lemeshow test for calibration. The regression task was evaluated by comparing median actual and predicted discharge, loss penalty function (LPF) ((actual-predicted)/actual) and calculating root mean squared relative errors (RMSRE). Results Median (P25-P75) ICU length of stay was 3 (2-5) days. For classification, the GP model showed an aROC of 0.758 which was significantly higher than the predictions by nurses, but not better than EuroSCORE and physicians. The GP had the best calibration, with a Brier Score of 0.179 and Hosmer-Lemeshow p-value of 0.382. For regression, GP had the highest proportion of patients with a correctly predicted day of discharge (40%), which was significantly better than the EuroSCORE (p < 0.001) and nurses (p = 0.044) but equivalent to physicians. GP had the lowest RMSRE (0.408) of all predictive models. Conclusions A GP model that uses PDMS data of the first 4 hours after admission in the ICU of scheduled adult cardiac surgery patients was able to predict discharge from the ICU as a classification as well as a regression task. The GP model demonstrated a significantly better discriminative power than the EuroSCORE and the ICU nurses, and at least as good as predictions done by ICU physicians. The GP model was the only well calibrated model.

Purpose: We estimated the 5-year overall, age at diagnosis- and stage-specific colorectal cancer survival in patients treated through their coverage with Seguro Popular., Methods: We conducted a retrospective study using a dataset that included 1418 colorectal cancer patients covered by Seguro Popular (Mexico's public health insurance system covering 60 % of the population) between 2013 and 2016. Deaths were identified using the Epidemiologic Death Statistics Subsystem registry, with a specialized algorithm for record linkage. The Kaplan-Meier method was used to estimate overall survival curves and the proportion of patients alive at various follow-up time points. We compared survival curves across subgroups using the log-rank test., Results: In this study the average age at diagnosis was 56 years with 31.9 % of patients diagnosed before the age of 50. Most cases (78.1 %) were diagnosed in advanced stages (i.e., III and IV), with nearly half of the cases originating in the rectum. The overall 5-year survival was 50 %, with higher survival (74 %) for patients with stage I-II and lower survival for those with stage III (58 %) and IV (33 %). While age at diagnosis was not associated with survival for early-stage colorectal cancer, younger patients with metastatic disease had a worse prognosis compared to older patients., Conclusion: The 5-year overall colorectal cancer survival was 50 %, with variation by clinical stage. Almost 80 % of the population was diagnosed with advanced stages, underscoring the need for screening programs. Younger patients with metastatic disease exhibited a worse prognosis, highlighting the need for targeted interventions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Use of fine-needle aspiration biopsy (FNAB) specimens on Xpert Breast Cancer STRAT4 Assay (STRAT4; Cepheid, Sunnyvale, CA, USA), a CE-marked in-vitro diagnostic medical device, could potentially increase access to breast cancer biomarker testing in resource-constrained settings. We aimed to assess the performance of a research use-only version of STRAT4 using FNAB specimens in Tanzania., Methods: In this prospective diagnostic accuracy study, patients aged 18 years or older with palpable breast masses presenting to the FNAB Clinic at Muhimbili National Hospital (Dar es Salaam, Tanzania) were recruited consecutively. Patients who were pregnant, lactating, or had a previous diagnosis of breast cancer were excluded. STRAT4 testing was performed on off-label FNAB samples using four protocols: the 1 × protocol (using the standard lysate method) on FNAB smears (1 × FNAB), quick lysis and Maui protocols (both on FNAB smears), and the 1 × protocol on formalin-fixed paraffin-embedded (FFPE) cell block material (1 × cell block). For 1 × FNAB and 1 × cell block, tissue was processed using FFPE lysis reagent, incubated at 80°C with proteinase K, and followed by addition of 95% or higher ethanol. Quick lysis was processed using FFPE lysis reagent and 95% or higher ethanol, whereas Maui was processed using a proprietary research-use only lysis reagent. The primary outcomes were overall concordance, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of STRAT4 as compared with immunohistochemistry or immunohistochemistry plus fluorescence in-situ hybridisation performed on cell blocks using clinically validated protocols in a Clinical Laboratory Improvement Amendments-accredited laboratory at the University of California, San Francisco (San Francisco, CA, USA)., Findings: Between Nov 29, 2017, and Dec 17, 2020, 208 patients were enrolled. Of 208 cases, 51 (25%) were excluded from analysis because of insufficient tissue in the cell block or absent cell blocks, leaving 157 participants (all female) for analysis. For oestrogen receptor, 1 × FNAB had the best performance, with an overall concordance of 95% (95% CI 90-100), sensitivity of 94% (85-100), specificity of 97% (90-100), and AUC of 0·96 (0·81-1·00). For progesterone receptor, 1 × cell block had the best overall performance (overall concordance 89% [95% CI 84-95], sensitivity 91% [82-99], and specificity 89% [81-97], with an AUC of 0·93 [0·89-0·99]) and 1 × FNAB performed the best among the smear protocols, with a concordance of 84% (95% CI 74-93), sensitivity of 63% (43-82), specificity of 97% (92-100), and AUC of 0·91 (0·72-0·97). For HER2, Maui had the highest agreement, with an overall concordance of 93% (95% CI 89-98), sensitivity of 96% (88-100), specificity of 92% (87-98), and AUC of 0·95 (0·98-1·00). For Ki67, Maui had the best performance of smear protocols, with a concordance of 73% (95% CI 64-82), sensitivity of 70% (58-81), specificity of 81% (66-96), and AUC of 0·80 (0·54-0·82)., Interpretation: Processing FNAB samples with STRAT4 is feasible in Tanzania, and performance for the oestrogen receptor is robust. Further optimisation of STRAT4 for FNAB has the potential to improve timely access to breast cancer diagnostics in resource-constrained settings., Funding: US National Institutes of Health; UCSF Global Cancer Program, Helen Diller Family Comprehensive Cancer Center; UCSF Department of Pathology; and Cepheid., Competing Interests: Declaration of interests KEH, JW, and MB are employees of Cepheid and own stock shares in Cepheid's parent company, Danaher. DLN and EV received funding, equipment, and study materials for the project from Cepheid. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Clinical practice guidelines are widely used in oncology to guide clinical decision making and inform health policy and planning. In recent years, the National Comprehensive Cancer Network and the American Society of Clinical Oncology, as well as other international groups, have developed resource-stratified guidelines to guide clinicians and policymakers on cancer diagnosis and management in settings with various levels of resource constraints. Current methods for developing resource-stratified guidelines rely heavily on supporting evidence originating from high-income countries. In this commentary, the authors discuss limitations of the existing methods to develop resource-stratified guidelines and offer perspective on ways to strengthen the guidelines and their evidence base. Pulling from conceptual frameworks in the health policy domain, the authors outline a more inclusive approach to evidence synthesis that seeks to integrate the growing volume of cancer research emerging from low- and middle-income countries. The authors also introduce a revised evidence framework that provides transparency into the generalizability of evidence within the guidelines. These changes have the potential to enhance resource-stratified guidelines and bring us one step closer to the goal of evidence-based guidelines that are appropriate for diverse settings and unique patient populations across the world., (© 2024 The Author(s). Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology , to patients seen in their own clinical practice.

Background: The incidence of breast and colorectal cancer (CRC) in younger-than-average-age patients is rising and poorly understood. This is the largest study on patients with both cancers who are less than 60 years old and aims to characterize demographic, clinicopathologic, and genetic features and describe therapeutic dilemmas and management strategies., Materials and Methods: This is a retrospective medical records review of patients at the University of California San Francisco with both primary breast and CRC before age 60., Results: Fifty-one patients were identified; 41 had detailed medical records. Median age of diagnosis with breast cancer was 43 (range 27-59) and CRC was 50 (28-59). Most were Caucasian (38, 74.5%) and never smokers (23, 56.1%); about half were current alcohol consumers (20, 48.8%) and about one-third had sedentary jobs (14, 34.1%). Average BMI was 25.8 (range: 14-49), and 30% were overweight or obese. Breast was the first cancer diagnosed in 36 patients (70.6%) and 44 (86.3%) had a metachronous CRC diagnosis. Breast cancer was early stage (0-2) in 32 (78.0%) patients whereas CRC was split between early stage (1-2) in 14 (34.1%) and later stage (3-4) in 19 (46.2%). Ten patients (24.3%) had a known germline mutation, although 23 (56.1%) had a family history of cancer in a first-degree relative., Conclusion: Younger patients with both breast and CRC are a unique cohort, often without known risk factors. Alcohol consumption and sedentary jobs were the most common risk factors, and about one-quarter had a known genetic predisposition. Comanagement of both cancers requires individualized, multidisciplinary care., (© The Author(s) 2024. Published by Oxford University Press.)