Analyses

A pre-specified meta-analysis of pooled, individual patient-level data from the DELIVER and DAPA-HF trials, testing dapagliflozin in patients with heart failure, demonstrates reductions in risk of cardiovascular-associated deaths and hospital admissions for heart failure, regardless of ejection fraction.

A large-scale population analysis quantifies the burden of mental illness and self-harm events in patients diagnosed with the most common adult cancers and highlights opportunities for advancing patient care.

A global analysis across 62 studies, of which 28 were meta-analyzed, reveals an increased risk of death by suicide in patients with cancer and underscores the need for comprehensive psycho-oncological therapy during clinical routine to improve the quality of life of patients.

Meta-analysis of cardiovascular secondary outcomes from the SURPASS program, testing efficacy of a new novel dual GIP/GLP-1 receptor agonist tirzepatide, demonstrates cardiovascular safety in patients with type 2 diabetes.

An analysis of COVID-19 vaccine allocation frameworks in the United States across 64 Centers for Disease Control and Prevention jurisdictions reveals that, as of 31 March 2021, 37 jurisdictions had adopted disadvantage indices to reduce health disparities. The analysis also highlights the importance of vaccine prioritization based on health and place.

An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.

A meta-analysis comparing primary efficacy outcomes of phase 2 and phase 3 randomized controlled trials in rheumatoid arthritis and psoriatic arthritis shows that phase 2 studies consistently overestimate the effect sizes anticipated in subsequent phase 3 trials.

Explicitly emulating a target trial using real-world data can avoid common biases in observational studies.

Analysis of the ExAC and 1000 Genomes data sets estimates the impact of inter-individual variation on the efficacy and safety of therapies based on CRISPR endonucleases.

HRDetect represents a model integrating whole-genome sequencing mutation signatures associated with BRCA1 and BRCA2 deficiency. The implementation of this predictor across different tumor types identifies a larger proportion of patients displaying ‘BRCAness’ than previously recognized; they might derive benefit from platinum and PARP-inhibitor therapies.

Systematic analysis of more than 5,900 human tumor exomes yields a new genomic classifier of microsatellite instability and insight into its prevalence and biological implications.

The authors develop a new method to mine genomic cancer data to uncover complex indels. These simultaneous deletions and insertions have been over-looked by previous sequencing data analysis methods, and the Pindel-C algorithm uncovers new information about their potential contribution to tumorigenesis.

The authors analyze the extent of intratumor heterogeneity across 12 tumor types to reveal that increased heterogeneity is a general phenomenon and has a biphasic contribution to tumor progression.

An international consortium of colorectal cancer researchers undertakes a large-scale data sharing project to achieve a consensus molecular classification of colorectal cancers.

Systematic analysis of cancer-associated mutations in the blood cells of healthy individuals.

What are the most important questions that the HIV field needs to answer to make progress? Nature Medicine asked this question to a group of HIV researchers to identify some of the key roadblocks in HIV research.