Radiation Proctitis in Patients With Locally Advanced Cervical Cancer Treated by Chemoradiation: Analysis and Predictive Factors From a Retrospective Cohort.

BACKGROUND: Radiation proctitis is a misunderstanding complication of chemoradiation in locally advanced cervical cancer. The objective of our study is to provide a detailed description and analysis of predictive factors associated with radiation proctitis in a retrospective cohort of patients treated by chemoradiation for locally advanced cervical cancer. METHODS: All patients treated by exclusive chemoradiation or chemoradiation followed by brachytherapy for locally advanced cervical cancer from 2011 to 2017 were included in the study. A bivariate analysis was conducted to establish correlations between the occurrence of radiation proctitis and various clinical and technical variables. RESULTS: A total of 128 patients were included in the study. The mean dose (SD) to the planning target volume was 47.1 Gy (6.2). Fifty-nine (46.1%) patients underwent brachytherapy. Sixteen patients (12.5%) developed radiation proctitis, grade 2 or higher in 12 patients (9.3%). In univariate analysis, anticoagulant or antiplatelet treatments (P=0.039), older age (P=0.049), rectal volume irradiated at 40 Gy (P=0.01) and 30 Gy (P=0.037) were significantly associated with the occurrence of a grade ≥2 radiation proctitis. The delivered dose to 2 cm3 of rectum (D2cm3) showed a potential association with the occurrence of radiation proctitis of all grades (P=0.064). CONCLUSION: This study highlights clinical and technical factors that should be considered in assessing the risk of radiation proctitis. These results contribute to a better understanding of this complication.

Protocol for fever control using external cooling in mechanically ventilated patients with septic shock: SEPSISCOOL II randomised controlled trial.

INTRODUCTION: Fever treatment is commonly applied in patients with sepsis but its impact on survival remains undetermined. Patients with respiratory and haemodynamic failure are at the highest risk for not tolerating the metabolic cost of fever. However, fever can help to control infection. Treating fever with paracetamol has been shown to be less effective than cooling. In the SEPSISCOOL pilot study, active fever control by external cooling improved organ failure recovery and early survival. The main objective of this confirmatory trial is to assess whether fever control at normothermia can improve the evolution of organ failure and mortality at day 60 of febrile patients with septic shock. This study will compare two strategies within the first 48 hours of septic shock: treatment of fever with cooling or no treatment of fever. METHODS AND ANALYSIS: SEPSISCOOL II is a pragmatic, investigator-initiated, adaptive, multicentre, open-label, randomised controlled, superiority trial in patients admitted to the intensive care unit with febrile septic shock. After stratification based on the acute respiratory distress syndrome status, patients will be randomised between two arms: (1) cooling and (2) no cooling. The primary endpoint is mortality at day 60 after randomisation. The secondary endpoints include the evolution of organ failure, early mortality and tolerance. The target sample size is 820 patients. ETHICS AND DISSEMINATION: The study is funded by the French health ministry and was approved by the ethics committee CPP Nord Ouest II (Amiens, France). The results will be submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04494074.

Fluid Intake in Critically Ill Patients: The "Save Useless Fluids For Intensive Resuscitation" Multicenter Prospective Cohort Study.

OBJECTIVES: Patients at risk of adverse effects related to positive fluid balance could benefit from fluid intake optimization. Less attention is paid to nonresuscitation fluids. We aim to evaluate the heterogeneity of fluid intake at the initial phase of resuscitation. DESIGN: Prospective multicenter cohort study. SETTING: Thirty ICUs across France and one in Spain. PATIENTS: Patients requiring vasopressors and/or invasive mechanical ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All fluids administered by vascular or enteral lines were recorded over 24 hours following admission and were classified in four main groups according to their predefined indication: fluids having a well-documented homeostasis goal (resuscitation fluids, rehydration, blood products, and nutrition), drug carriers, maintenance fluids, and fluids for technical needs. Models of regression were constructed to determine fluid intake predicted by patient characteristics. Centers were classified according to tertiles of fluid intake. The cohort included 296 patients. The median total volume of fluids was 3546 mL (interquartile range, 2441-4955 mL), with fluids indisputably required for body fluid homeostasis representing 36% of this total. Saline, glucose-containing high chloride crystalloids, and balanced crystalloids represented 43%, 27%, and 16% of total volume, respectively. Whatever the class of fluids, center of inclusion was the strongest factor associated with volumes. Compared with the first tertile, the difference between the volume predicted by patient characteristics and the volume given was +1.2 ± 2.0 L in tertile 2 and +3.0 ± 2.8 L in tertile 3. CONCLUSIONS: Fluids indisputably required for body fluid homeostasis represent the minority of fluid intake during the 24 hours after ICU admission. Center effect is the strongest factor associated with the volume of fluids. Heterogeneity in practices suggests that optimal strategies for volume and goals of common fluids administration need to be developed.

Size and Predictive Factors of Microscopic Tumor Extension in Locally Advanced Non-Small Cell Lung Cancer.

PURPOSE: Radiation therapy for locally advanced non-small cell lung cancer (NSCLC) should treat the whole tumor, including its microscopic extensions, and protect adjacent organs at risk as much as possible. The aim of our study is to evaluate the size of microscopic tumor extension (MEmax) in NSCLC, and search for potential predictive factors. METHODS AND MATERIALS: We retrospectively selected 70 patients treated with postoperative radiation therapy for a NSCLC with N2 nodal status, then 34 additional patients operated for a squamous cell lung cancer with N1 or N2 nodal status. On the digitized slides originating from the resected tumors of these 104 patients, we outlined the border of the tumor, as seen with the naked eye. We then searched for microscopic tumor extension outside of these borders with a magnification as high as 40 × and measured the maximum size of MEmax. RESULTS: The median MEmax in the whole cohort was 0.85 mm (0-9.95). The MEmax was <5.3 mm in 95% of adenocarcinomas (6.5 mm in the subgroup without neoadjuvant chemotherapy) and <3.5 mm in 95% of squamous cell carcinomas (3.7 mm in the subgroup without neoadjuvant chemotherapy). After multivariate analysis, the factors associated with the size of MEmax were vascular invasion (P = .0002), histologic type, with a wider MEmax for adenocarcinomas in comparison with squamous cell carcinomas (P = .002), tumor size, which was inversely related with the size of MEmax (P = .024), and high blood pressure (P = .03). Macroscopic histologic tumor size was well correlated with both radiologic tumor size on a mediastinal setting computed tomography (correlation coefficient of 0.845) and on a parenchymal setting computed tomography (correlation coefficient of 0.836). CONCLUSIONS: The clinical target volume margin, accounting for microscopic tumoral extension, could be reduced to 7 mm for adenocarcinomas and 4 mm for squamous cell carcinomas.

Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate.

Background: The Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) have recognized social media as a new data source to strengthen their activities regarding drug safety. Objective: Our objective in the ADR-PRISM project was to provide text mining and visualization tools to explore a corpus of posts extracted from social media. We evaluated this approach on a corpus of 21 million posts from five patient forums, and conducted a qualitative analysis of the data available on methylphenidate in this corpus. Methods: We applied text mining methods based on named entity recognition and relation extraction in the corpus, followed by signal detection using proportional reporting ratio (PRR). We also used topic modeling based on the Correlated Topic Model to obtain the list of the matics in the corpus and classify the messages based on their topics. Results: We automatically identified 3443 posts about methylphenidate published between 2007 and 2016, among which 61 adverse drug reactions (ADR) were automatically detected. Two pharmacovigilance experts evaluated manually the quality of automatic identification, and a f-measure of 0.57 was reached. Patient's reports were mainly neuro-psychiatric effects. Applying PRR, 67% of the ADRs were signals, including most of the neuro-psychiatric symptoms but also palpitations. Topic modeling showed that the most represented topics were related to Childhood and Treatment initiation, but also Side effects. Cases of misuse were also identified in this corpus, including recreational use and abuse. Conclusion: Named entity recognition combined with signal detection and topic modeling have demonstrated their complementarity in mining social media data. An in-depth analysis focused on methylphenidate showed that this approach was able to detect potential signals and to provide better understanding of patients' behaviors regarding drugs, including misuse.

Mining Adverse Drug Reactions in Social Media with Named Entity Recognition and Semantic Methods.

Suspected adverse drug reactions (ADR) reported by patients through social media can be a complementary source to current pharmacovigilance systems. However, the performance of text mining tools applied to social media text data to discover ADRs needs to be evaluated. In this paper, we introduce the approach developed to mine ADR from French social media. A protocol of evaluation is highlighted, which includes a detailed sample size determination and evaluation corpus constitution. Our text mining approach provided very encouraging preliminary results with F-measures of 0.94 and 0.81 for recognition of drugs and symptoms respectively, and with F-measure of 0.70 for ADR detection. Therefore, this approach is promising for downstream pharmacovigilance analysis.