Notes

Self-assembling peptide hydrogel SPG-178 as being a pancreatic fistula-preventing agent.
Among 243 patients from KEYNOTE-010 and 782 from Flatiron, median age was 63
68 years, and 64%
54% were male, respectively. OS data from KEYNOTE-010 and Flatiron were similar without any adjustment (n = 782; hazard ratio [HR], 0.96; 95% CI, 0.80 to 1.15) and after both filtering and propensity adjustment (n = 221; HR, 0.99; 95% CI, 0.73 to 1.34).

Without any adjustment, as well as after applying similar EC and appropriate statistical methods, RWD demonstrated similar effectiveness for pembrolizumab in second-line NSCLC as observed in randomized clinical trials.
Without any adjustment, as well as after applying similar EC and appropriate statistical methods, RWD demonstrated similar effectiveness for pembrolizumab in second-line NSCLC as observed in randomized clinical trials.
Using novel Bayesian adaptive designs has great potential to improve the efficiency of early-phase clinical trials. A major barrier for clinical researchers to adopt novel designs is the lack of easy-to-use software. Our purpose is to develop a user-friendly software platform to implement novel clinical trial designs that address various challenges in early-phase dose-finding trials.

We used
to develop a web-based software platform to facilitate the use of recent novel adaptive designs.

We developed a web-based software suite, called Bayesian optimal interval (BOIN) suite, which includes R Shiny applications to handle various clinical settings, including single-agent phase I trials with and without prior information, trials with late-onset toxicity, trials to find the optimal biological dose based on risk-benefit trade-off, and drug combination trials to find a single maximum tolerated dose (MTD) or the MTD contour. The applications are built using the same software architecture to ensure the best anonly advances the clinical research and drug development by facilitating the use of novel trial designs with optimal performance but also enhances collaborations between biostatisticians and clinicians by disseminating novel statistical methodology to broader scientific communities through user-friendly software. The BOIN suite establishes a KISS principle keep it simple, but smart.
Neoadjuvant chemotherapy (NAC) is used to treat locally advanced breast cancer (LABC) and high-risk early breast cancer (BC). Pathological complete response (pCR) has prognostic value depending on BC subtype. Rates of pCR, however, can be variable. Predictive modeling is desirable to help identify patients early who may have suboptimal NAC response. Here, we test and compare the predictive performances of machine learning (ML) prediction models to a standard statistical model, using clinical and pathological data.

Clinical and pathological variables were collected in 431 patients, including tumor size, patient demographics, histological characteristics, molecular status, and staging information. A standard multivariable logistic regression (MLR) was developed and compared with five ML models k-nearest neighbor classifier, random forest (RF) classifier, naive Bayes algorithm, support vector machine, and multilayer perceptron model. Model performances were measured using a receiver operating characteristic nstrated the best predictive performance among all models.
We developed a system to automate analysis of the clinical oncology scientific literature from bibliographic databases and match articles to specific patient cohorts to answer specific questions regarding the efficacy of a treatment. The approach attempts to replicate a clinician's mental processes when reviewing published literature in the context of a patient case. We describe the system and evaluate its performance.

We developed separate ground truth data sets for each of the tasks described in the paper. The first ground truth was used to measure the natural language processing (NLP) accuracy from approximately 1,300 papers covering approximately 3,100 statements and approximately 25 concepts; performance was evaluated using a standard F1 score. The ground truth for the expert classifier model was generated by dividing papers cited in clinical guidelines into a training set and a test set in an 8020 ratio, and performance was evaluated for accuracy, sensitivity, and specificity.

The NLP models were volving science.
Neutropenia is a serious complication of chemotherapy in patients with solid tumors. Panobinostat in vivo The influence of hospital volume on outcomes in patients with neutropenia has been little investigated. We hypothesized that large-volume hospitals would have reduced mortality rates for neutropenic patients compared with small-volume institutions.

We used the Nationwide Inpatient Sample database of the Healthcare Cost and Utilization Project, for the years 2007-2011. All adult inpatient episodes with a diagnosis of both neutropenia and solid-tumor malignancy were included. Hospital volume was defined as the number of neutropenic cancer episodes per institution per year. Mortality was defined as death during admission. A multilevel mixed-effects logistic regression model was applied.

Twenty thousand three hundred and ten hospitalizations were included in the study, from 1,869 different institutions. Median age was 62 years. The overall inpatient mortality was 2.3%, and was dependent on age (age 50-59 years-1.6% and age lidate our findings or overcome potential biases, understand mechanism, and investigate how smaller institutions can improve outcomes.
As oxaliplatin results in cumulative neurotoxicity, reducing treatment duration without loss of efficacy would benefit patients and healthcare providers.

Four of the six studies in the International Duration of Adjuvant Chemotherapy (IDEA) collaboration included patients with high-risk stage II colon and rectal cancers. Patients were treated (clinician and/or patient choice) with either fluorouracil, leucovorin, and oxaliplatin (FOLFOX) or capecitabine and oxaliplatin (CAPOX) and randomly assigned to receive 3- or 6-month treatment. The primary end point is disease-free survival (DFS), and noninferiority of 3-month treatment was defined as a hazard ratio (HR) of < 1.2-
6-month arm. To detect this with 80% power at a one-sided type one error rate of 0.10, a total of 542 DFS events were required.

3,273 eligible patients were randomly assigned to either 3- or 6-month treatment with 62% receiving CAPOX and 38% FOLFOX. There were 553 DFS events. Five-year DFS was 80.7% and 83.9% for 3-month and 6-month treatment, respectively (HR, 1.
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