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Background: Preclinical research has identified the mechanisms via which bacteria influence cancer treatment outcomes. Clinical studies have demonstrated the potential to modify the microbiome in cancer treatment. Herein, we systematically analyze how gut microorganisms interact with chemotherapy and immune checkpoint inhibitors, specifically focusing on how gut bacteria affect the pharmacokinetics and pharmacodynamics of cancer treatment. Method: This study searched Web of Science, Scopus, and PubMed until August 2023. Studies were screened by their title and abstract using the Rayyan intelligent tool for systematic reviews. Quality assessment of studies was done using the JBI critical appraisal tool. Result: Alterations in the gut microbiome are associated with gastric cancer and precancerous lesions. These alterations include reduced microbial alpha diversity, increased bacterial overgrowth, and decreased richness and evenness of gastric bacteria. Helicobacter pylori infection is associated with reduced richness and evenness of gastric bacteria, while eradication only partially restores microbial diversity. The gut microbiome also affects the response to cancer treatments, with higher abundances of Lactobacillus associated with better response to anti-PD-1/PD-L1 immunotherapy and more prolonged progression-free survival. Antibiotic-induced gut microbiota dysbiosis can reduce the anti-tumor efficacy of 5-Fluorouracil treatment, while probiotics did not significantly enhance it. A probiotic combination containing Bifidobacterium infantis, Lactobacillus acidophilus, Enterococcus faecalis, and Bacillus cereus can reduce inflammation, enhance immunity, and restore a healthier gut microbial balance in gastric cancer patients after partial gastrectomy. Conclusion: Probiotics and targeted interventions to modulate the gut microbiome have shown promising results in cancer prevention and treatment efficacy.Systematic review registration: https://osf.io/6vcjp.

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Objective: Epidermolysis bullosa acquisita (EBA) is a rare dermatosis of the mucous membrane and/or skin. Employing biologic treatment modalities, specifically rituximab (RTX), have become pivotal measure in treating patients with blistering diseases. This study aims to summarize the current evidence on the safety and efficacy of RTX in EBA. Methods: An extensive search was performed in MEDLINE/PubMed, Embase, Scopus, and Web of Science databases until the end of August 19th, 2023. Two independent reviewers screened the papers, and collected data. Two hundred thirty-three studies were screened using Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Results: Thirty-one studies were enrolled. The most common reason of RTX administration in patients with EBA was recalcitrant diseases. Clinical response and disease remission was recorded as 92.7 percent (63 patients) and 73.8 percent (45 patients) of the patients, respectively. A relapse rate of 39.5 percent (15 patients) in the mean follow-up of 23.0 months was reported in the studies. Of the patients, 28.2 percent (11 patients) experienced RTX-related side events, mostly mild and transient infusion reactions. Conclusion: The results of this systematic review demonstrated that RTX is safe and effective in patients with EBA. This biological treatment modality can be routinely used in managing EBA.

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BACKGROUND: The recent pandemic had the potential to worsen the opioid crisis through multiple effects on patients' lives, such as the disruption of care. In particular, good levels of adherence with respect to medication for opioid use disorder (MOUD), recognized as being important for positive outcomes, may be disrupted. OBJECTIVE: This study aimed to investigate whether patients on MOUD experienced a drop in medication adherence during the recent COVID-19 pandemic. METHODS: This retrospective cohort study used Medicaid claims data from 6 US states from 2018 until the start of 2021. We compared medication adherence for people on MOUD before and after the beginning of the COVID-19 pandemic in March 2020. Our main measure was the proportion of days covered (PDC), a score that measures patients' adherence to their MOUD. We carried out a breakpoint analysis on PDC, followed by a patient-level beta regression analysis with PDC as the dependent variable while controlling for a set of covariates. RESULTS: A total of 79,991 PDC scores were calculated for 37,604 patients (age: mean 37.6, SD 9.8 years; sex: n=17,825, 47.4% female) between 2018 and 2021. The coefficient for the effect of COVID-19 on PDC score was -0.076 and was statistically significant (odds ratio 0.925, 95% CI 0.90-0.94). CONCLUSIONS: The COVID-19 pandemic was negatively associated with patients' adherence to their medication, which had declined since the beginning of the pandemic.

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BACKGROUND: Opioid Use Disorder (OUD) and opioid overdose (OD) impose huge social and economic burdens on society and health care systems. Research suggests that Medication for Opioid Use Disorder (MOUD) is effective in the treatment of OUD. We use machine learning to investigate the association between patient's adherence to prescribed MOUD along with other risk factors in patients diagnosed with OUD and potential OD following the treatment. METHODS: We used longitudinal Medicaid claims for two selected US states to subset a total of 26,685 patients with OUD diagnosis and appropriate Medicaid coverage between 2015 and 2018. We considered patient age, sex, region level socio-economic data, past comorbidities, MOUD prescription type and other selected prescribed medications along with the Proportion of Days Covered (PDC) as a proxy for adherence to MOUD as predictive variables for our model, and overdose events as the dependent variable. We applied four different machine learning classifiers and compared their performance, focusing on the importance and effect of PDC as a variable. We also calculated results based on risk stratification, where our models separate high risk individuals from low risk, to assess usefulness in clinical decision-making. RESULTS: Among the selected classifiers, the XGBoost classifier has the highest AUC (0.77) closely followed by the Logistic Regression (LR). The LR has the best stratification result: patients in the top 10% of risk scores account for 35.37% of overdose events over the next 12 month observation period. PDC score calculated over the treatment window is one of the most important features, with better PDC lowering risk of OD, as expected. In terms of risk stratification results, of the 35.37% of overdose events that the predictive model could detect within the top 10% of risk scores, 72.3% of these cases were non-adherent in terms of their medication (PDC <0.8). Targeting the top 10% outcome of the predictive model could decrease the total number of OD events by 10.4%. CONCLUSIONS: The best performing models allow identification of, and focus on, those at high risk of opioid overdose. With MOUD being included for the first time as a factor of interest, and being identified as a significant factor, outreach activities related to MOUD can be targeted at those at highest risk.

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Physical activity (PA) is a key component of a healthy life, and it is hypothesised that individuals with higher levels of PA utilise fewer hospital resources. Quantifying the association between PA and hospital resource use is of interest to both payers and planners but estimates of its size in the general population are rare. In this paper we provide estimates of the association between PA and payments to hospitals in the Australian population over age 45. We use data from 45 and Up Study, a survey that contains health and lifestyle factors information about approximately 260,000 individuals over age 45 living in NSW, linked to hospital and death data. The linked data set allows to define a unique indicator for the level of PA over the week prior to the survey interview and to calculate payments to hospitals over the next year. We use Coarsened Exact Matching and multivariate analysis to study the relationship between PA and hospital payments, controlling for chronic health conditions, risk factors, standard socioeconomic variables and death. Our results clearly indicate that there is a statistically significant association between PA and lower hospital payments. While the size of the association depends to some extent on the covariates used in the model the conclusions are robust to changes in model specification. We also perform a sub-group analysis and show that the cost savings associated with PA are significantly larger for older and lower income populations. This study shows that if one is interested in lowering hospital expenditures then increasing PA levels is a policy that has the potential of being effective. It also shows that one does not need to target the entire population to achieve cost savings but can limit the intervention to the older population and/or the one in the lowest socioeconomic status.

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A healthy youngwoman presented 3 days after a jet ski accident with a large left vulvar haematoma measuring 12 cm. Immediately postinjury, she was managed conservatively in the emergency room of another hospital. However, the haematoma continued to slowly expand. She presented to our clinic with difficulty walking and severe discomfort. Decision was made to drain the haematoma surgically. The patient was sceptical to have scarring on her vulva. Thus, the haematoma was evacuated by a vertical incision on the left vaginal sidewall. After evacuation and achieving haemostasis, the was closed with two interrupted sutures. Edges of the incision were secured similar to marsupialisation with five interrupted sutures to allow continual drainage. Her discomfort resolved immediately postsurgery and she had an uncomplicated postoperative course. The intravaginal approach yielded superior aesthetic result with no scarring on the external vulva.

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