Open Access

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.

Background: The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. Methods: We used 115 complete datasets from MCI patients of the "Dementia Competence Network", a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Results: Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. Conclusion: A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.

Extensive black shale deposits formed in the Early Cretaceous South Atlantic, supporting the notion that this emerging ocean basin was a globally important site of organic carbon burial. The magnitude of organic carbon burial in marine basins is known to be controlled by various tectonic, oceanographic, hydrological, and climatic processes acting on different temporal and spatial scales, the nature and relative importance of which are poorly understood for the young South Atlantic. Here we present new bulk and molecular geochemical data from an Aptian–Albian sediment record recovered from the deep Cape Basin at Deep Sea Drilling Project (DSDP) Site 361, which we combine with general circulation model results to identify driving mechanisms of organic carbon burial. A multi-million year decrease (i.e. Early Aptian–Albian) in organic carbon burial, reflected in a lithological succession of black shale, gray shale, and red beds, was caused by increasing bottom water oxygenation due to abating tectonic restriction via South Atlantic-Southern Ocean gateways. These results emphasize basin evolution and ocean gateway development as a decisive primary control on enhanced organic carbon preservation in the Cape Basin at geological time scales (>1 Myr). The Early Aptian black shale sequence comprises alternations of shales with high (>5%) and relatively low (~3%) organic carbon content of marine sources, the former being deposited during the global Oceanic Anoxic Event (OAE) 1a, as well as during repetitive events before and after OAE 1a. In all cases, these short-term events of enhanced organic carbon burial coincided with strong influxes of sediments derived from the proximal African continent, indicating closely coupled climate–land–ocean interactions. Supported by our model results, we propose that fluctuations in weathering-derived nutrient input from the southern African continent, linked to fluctuations in pCO2 and/or orbitally driven humidity/aridity, were the underlying drivers of short-term organic carbon burial in the deep Cape Basin. These results suggest that deep marine environments of emerging ocean basins responded sensitively and directly to short term fluctuations in riverine nutrient fluxes. We explain this relationship by the lack of wide and mature continental shelf seas that could have acted as a barrier or filter for nutrient transfer from the continent into the deep ocean.

Maintenance therapy after allogeneic hematopoietic stem cell transplantation (HSCT) for acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS) is conceptually attractive to prevent relapse, but has been hampered by the limited number of suitable anti-leukemic agents. The deacetylase inhibitor (DACi) panobinostat demonstrated moderate anti-leukemic activity in a small subset of patients with advanced AML and high-risk MDS in phase I/II trials.1, 2 It also displays immunomodulatory activity3 that may enhance leukemia-specific cytotoxicity4 and mitigate graft versus host disease (GvHD), but conversely could impair T- and NK cell function.5, 6 We conducted this open-label, multi-center phase I/II trial (NCT01451268) to assess the feasibility and preliminary efficacy of prolonged prophylactic administration of panobinostat after HSCT for AML or MDS. The study protocol was approved by an independent ethics committee and conducted in compliance with the Declaration of Helsinki. All patients provided written informed consent. ...

Introduction Occurrence of inaccurate or delayed diagnoses is a significant concern in patient care, particularly in emergency medicine, where decision making is often constrained by high throughput and inaccurate admission diagnoses. Artificial intelligence-based diagnostic decision support system have been developed to enhance clinical performance by suggesting differential diagnoses to a given case, based on an integrated medical knowledge base and machine learning techniques. The purpose of the study is to evaluate the diagnostic accuracy of Ada, an app-based diagnostic tool and the impact on patient outcome. Methods and analysis The eRadaR trial is a prospective, double-blinded study with patients presenting to the emergency room (ER) with abdominal pain. At initial contact in the ER, a structured interview will be performed using the Ada-App and both, patients and attending physicians, will be blinded to the proposed diagnosis lists until trial completion. Throughout the study, clinical data relating to diagnostic findings and types of therapy will be obtained and the follow-up until day 90 will comprise occurrence of complications and overall survival of patients. The primary efficacy of the trial is defined by the percentage of correct diagnoses suggested by Ada compared with the final discharge diagnosis. Further, accuracy and timing of diagnosis will be compared with decision making of classical doctor–patient interaction. Secondary objectives are complications, length of hospital stay and overall survival. Ethics and dissemination Ethical approval was received by the independent ethics committee (IEC) of the Goethe-University Frankfurt on 9 April 2020 including the patient information material and informed consent form. All protocol amendments must be reported to and adapted by the IEC. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings. Trial registration number DRKS00019098.