Background and objectivesRates of malignant melanoma are continuing to increase, and until recently effective treatments were lacking. However, since 2011 three immunotherapeutic agents, known as checkpoint inhibitors, have been approved. This review aims to establish whether these three drugs – ipilimumab, nivolumab, and pembrolizumab – offer greater efficacy and tolerability compared to control interventions (placebo, immunotherapy, or chemotherapy) in patients with stage III or IV unresectable cutaneous melanoma.Materials and methodsA search on four major medical and scientific databases yielded 7,553 records, of which seven met the inclusion criteria, with a total study population of 3,628. Only prospective Phase II or III randomized controlled trials on checkpoint inhibitors for patients with unresectable cutaneous melanoma that reported data on survival (overall or progression-free), tumor response, or adverse events were included. Three meta-analyses were carried out.ResultsThe hazard ratio for progression or death was 0.54 (95% confidence interval [CI]: 0.44–0.67), and the odds ratio for best overall response rate was 4.48 (95% CI: 2.77–7.24), both in favor of checkpoint inhibitors. However, control treatments were associated with an insignificantly lower rate of discontinuation of treatment due to adverse effects or treatment-related adverse events (odds ratio =1.63 [95% CI: 0.55–4.88]).ConclusionThis study finds that checkpoint inhibitors are more effective than control interventions, both in terms of survival and tumor response, and yet no less tolerable. PD1 therapies (nivolumab and pembrolizumab) appear to offer greater efficacy than CTLA4 therapy (ipilimumab). The combination of nivolumab and ipilimumab was, however, the most effective, but significantly less tolerable than monotherapy. The lack of published clinical data does, however, limit this study. Further research is needed in two areas in particular: 1) to determine the optimal use of checkpoint inhibitors, specifically in terms of combination therapy, and 2) to identify reliable biomarkers to predictive responders and guide treatment assignment.

Many first trimester sporadic miscarriages are unexplained and the role of environmental exposures is unknown. The present aim was to study if levels of Perfluoroalkyl substances (PFASs) in early pregnancy are associated with unexplained, sporadic first trimester miscarriage. The study was performed within the Swedish SELMA pregnancy cohort. Seventy-eight women with non-recurrent first trimester miscarriage were included and 1449 women were available as live birth controls. Eight PFASs were measured in first trimester serum. A doubling of perfluorooctanoic acid (PFOA) exposure, corresponding to an inter-quartile increase, was associated with an odds ratio (95%CI) for miscarriage of 1.48 (1.09–2.01) when adjusting for parity, age and smoking. Analyses per quartiles of PFOA exposure indicated a monotonic dose response association with miscarriage. A similar, but not significant, pattern was observed for perfluorononanoic acid (PFNA). For other PFAS, there were no associations with miscarriage. We have previously shown associations between early pregnancy PFAS exposures and preeclampsia, as well as lower birth weight. Now we report an association between PFOA and miscarriage within the same cohort, which may suggest shared but unknown mechanisms. The study can only represent a period of early placentation and clinical pregnancy loss during the second half of the first trimester.

Background Sepsis is a life-threatening condition, causing almost one fifth of all deaths worldwide. The aim of the current study was to identify variables predictive of 7- and 30-day mortality among variables reflective of the presentation of septic patients arriving to the emergency department (ED) using machine learning. Methods Retrospective cross-sectional design, including all patients arriving to the ED at Södersjukhuset in Sweden during 2013 and discharged with an International Classification of Diseases (ICD)-10 code corresponding to sepsis. All predictions were made using a Balanced Random Forest Classifier and 91 variables reflecting ED presentation. An exhaustive search was used to remove unnecessary variables in the final model. A 10-fold cross validation was performed and the accuracy was described using the mean value of the following: AUC, sensitivity, specificity, PPV, NPV, positive LR and negative LR. Results The study population included 445 septic patients, randomised to a training (n = 356, 80%) and a validation set (n = 89, 20%). The six most important variables for predicting 7-day mortality were: “fever”, “abnormal verbal response”, “low saturation”, “arrival by emergency medical services (EMS)”, “abnormal behaviour or level of consciousness” and “chills”. The model including these variables had an AUC of 0.83 (95% CI: 0.80–0.86). The final model predicting 30-day mortality used similar six variables, however, including “breathing difficulties” instead of “abnormal behaviour or level of consciousness”. This model achieved an AUC = 0.80 (CI 95%, 0.78–0.82). Conclusions The results suggest that six specific variables were predictive of 7- and 30-day mortality with good accuracy which suggests that these symptoms, observations and mode of arrival may be important components to include along with vital signs in a future prediction tool of mortality among septic patients presenting to the ED. In addition, the Random Forests appears to be a suitable machine learning method on which to build future studies.

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