Citations

PURPOSE Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk prediction models have been developed using retrospective clinical data and have evolved significantly over the years in terms of predictors of recurrence, data usage, and predictive techniques (statistical/machine learning [ML]). METHODS Following PRISMA guidelines, we performed a systematic literature review of the aforementioned statistical and ML models published between January 2008 and December 2022 through searching five digital databases—PubMed, ScienceDirect, Scopus, Cochrane, and Web of Science. The comprehensive search yielded a total of 163 papers and after a screening process focusing on papers that dealt exclusively with statistical/ML methods, only 23 papers were deemed appropriate for further analysis. We benchmarked the studies on the basis of development, evaluation metrics, and validation strategy with an added emphasis on racial diversity of patients included in the studies. RESULTS In total, 30.4% of the included studies use statistical techniques, while 69.6% are ML-based. Among these, traditional ML models (support vector machines, decision tree, logistic regression, and naïve Bayes) are the most frequently used (26.1%) along with deep learning (26.1%). Deep learning and ensemble learning provide the most accurate predictions (AUC = 0.94 each). CONCLUSION ML-based prediction models exhibit outstanding performance, yet their practical applicability might be hindered by limited interpretability and reduced generalization. Moreover, predictive models for BC recurrence often focus on limited variables related to tumor, treatment, molecular, and clinical features. Imbalanced classes and the lack of open-source data sets impede model development and validation. Furthermore, existing models predominantly overlook African and Middle Eastern populations, as they are trained and validated mainly on Caucasian and Asian patients.

ABSTRACT The survival rates of many cancers have significantly improved due to recent advancements in cancer screening and therapeutics. Although better cancer outcomes are encouraging, additional health challenges have surfaced, the utmost of which is the burden imposed by various cardiovascular and renal toxicities of anticancer therapies. To improve the overall outcome of patients with cancer, it is essential to understand and manage these treatment-related adverse effects. The cardiovascular side effects of antineoplastic therapies are well-known and include left ventricular dysfunction, heart failure, myocardial ischaemia, QT prolongation, arrhythmia and hypertension. Among these, hypertension is the most common complication, prevalent in about 40% of all cancer patients, yet frequently overlooked and undertreated. This review explores the intricate connection between cancer and hypertension and provides distinct approaches to diagnosing, monitoring and managing hypertension in patients with cancer. We also outline the challenges and considerations that are relevant to the care of patients receiving anticancer drugs with prohypertensive potential.

Considering recently published data, this letter to the editor highlights the clinical relevance of CDK12 pathogenic or likely pathogenic mutations, noting that Black men have prostate cancers with increased rates of this pathologic alteration. Practitioners should be made aware of recent findings, given that CDK12 mutations are known to be associated with aggressive variants of prostate cancer and that they may confer susceptibility to PD-1 antagonists.

ImportanceParkinsonism and Parkinson disease (PD) are known to result from repetitive head impacts from boxing. Repetitive head impacts from American football may also be associated with increased risk of neurodegenerative pathologies that cause parkinsonism, yet in vivo research on the association between football play and PD is scarce and limited by small samples and equivocal findings.ObjectiveTo evaluate the association between football participation and self-reported parkinsonism or PD diagnosis.Design, Setting, and ParticipantsThis cross-sectional study leveraged data from the online Fox Insight study. Participants completed online questionnaires and self-reported whether they currently had a diagnosis of Parkinson disease or parkinsonism by a physician or other health care professional. In November 2020, the Boston University Head Impact Exposure Assessment was launched for data collection on repetitive head impacts. Data used for this manuscript were obtained from the Fox Insight database on June 9, 2022. A total of 1875 men who endorsed playing any organized sport were included. Former athletes were divided into those who participated in football (n = 729 [38.9%]) and those who participated in other sports (reference group).ExposuresSelf-reported participation in football, duration and level of football play, age at first exposure.Main Outcomes and MeasuresLogistic regression tested associations between PD status and history of football play, duration of football play, highest level played, and age at first exposure, controlling for age, education, history of diabetes or heart disease, body mass index, history of traumatic brain injury with loss of consciousness, and family history of PD.ResultsIn this sample of 1875 men (mean [SD] age, 67.69 [9.84] years) enriched for parkinsonism or PD (n = 1602 [85.4%]), 729 (38.9%) played football (mean [SD] duration, 4.35 [2.91] years). History of playing football was associated with higher odds of having a parkinsonism or PD diagnosis (odds ratio [OR], 1.61; 95% CI, 1.19-2.17). Among the entire sample, longer duration of play was associated with higher odds of having a parkinsonism or PD diagnosis (OR, 1.12; 95% CI, 1.06-1.19). Among football players, longer duration of football play (OR, 1.12; 95% CI, 1.02-1.23) and higher level of play (OR, 2.93; 95% CI, 1.28-6.73) were associated with higher odds of having parkinsonism or PD.Conclusions and RelevanceIn this cross-sectional study of participants enriched for PD, participation in football was associated with higher odds of having a reported parkinsonism or PD diagnosis.

Abstract Background Despite clinically demonstrated accuracy in next generation sequencing (NGS) data, many clinical laboratories continue to confirm variants with Sanger sequencing, which increases cost of testing and turnaround time. Several studies have assessed the accuracy of NGS in detecting single nucleotide variants; however, less has been reported about insertion, deletion, and deletion-insertion variants (indels). Methods We performed a retrospective analysis from 2015–2022 of indel results from a subset of NGS targeted gene panel tests offered through the Mayo Clinic Genomics Laboratories. We compared results from NGS and Sanger sequencing of indels observed in clinical runs and during the intra-assay validation of the tests. Results Results demonstrated 100% concordance between NGS and Sanger sequencing for over 490 indels (217 unique), ranging in size from 1 to 68 basepairs (bp). The majority of indels were deletions (77%) and 1 to 5 bp in length (90%). Variant frequencies ranged from 11.4% to 67.4% and 85.1% to 100% for heterozygous and homozygous variants, respectively, with a median depth of coverage of 2562×. A subset of indels (7%) were located in complex regions of the genome, and these were accurately detected by NGS. We also demonstrated 100% reproducibility of indel detection (n = 179) during intra-assay validation. Conclusions Together this data demonstrates that reportable indel variants up to 68 bp can be accurately assessed using NGS, even when they occur in complex regions. Depending on the complexity of the region or variant, Sanger sequence confirmation of indels is usually not necessary if the variants meet appropriate coverage and allele frequency thresholds.

The utilization of transcatheter aortic valve implantation (TAVI) has become the treatment of choice in patients with severe aortic stenosis (AS) with intermediate-to-high surgical risk for surgical aortic valve replacement (SAVR) [...]

The association and interaction between the central nervous system (CNS) and enteric nervous system (ENS) is well established. Essentially ENS is the second brain, as we call it. We tried to understand the structure and function, to throw light on the functional aspect of neurons, and address various disease manifestations. We summarized how various neurological disorders influence the gut via the enteric nervous system and/or bring anatomical or physiological changes in the enteric nervous system or the gut and vice versa. It is known that stress has an effect on Gastrointestinal (GI) motility and causes mucosal erosions. In our literature review, we found that stress can also affect sensory perception in the central nervous system. Interestingly, we found that mutations in the neurohormone, serotonin (5-HT), would result in dysfunctional organ development and further affect mood and behavior. We focused on the developmental aspects of neurons and cognition and their relation to nutritional absorption via the gastrointestinal tract, the development of neurodegenerative disorders in relation to the alteration in gut microbiota, and contrariwise associations between CNS disorders and ENS. This paper further summarizes the synergetic relation between gastrointestinal and neuropsychological manifestations and emphasizes the need to include behavioral therapies in management plans.