Trends in breast, colon, pancreatic, and uterine cancers in women during the COVID-19 pandemic in North Carolina

Importance: The COVID-19 pandemic led to reductions in primary care and cancer screening visits, which may delay detection of some cancers. The impact on incidence has not been fully quantified. We examined change in cancer incidence to determine how the COVID-19 pandemic may have altered the characteristics of cancers diagnosed among women. Methods: This study included female patients aged ≥18 years and diagnosed with breast (n = 9489), colon (n = 958), pancreatic (n = 669), or uterine (n = 1991) cancer at three hospitals in North Carolina. Using interrupted time series, we compared incidence of cancers diagnosed between March 2020 and November 2020 (during pandemic) with cancers diagnosed between January 2016 and February 2020 (pre-pandemic). Results: During the pandemic, incidence of breast and uterine cancers was significantly lower than expected compared to pre-pandemic (breast—18%, p = 0.03; uterine −20%, p = 0.05). Proportions of advanced pathologic stage and hormone receptor-negative breast cancers, and advanced clinical stage and large size uterine cancers were more prevalent during the pandemic. No significant changes in incidence were detected for pancreatic (−20%, p = 0.08) or colon (+14%, p = 0.30) cancers. Conclusion and Relevance: In women, the COVID-19 pandemic resulted in a significant reduction in the incidence of breast and uterine cancers, but not colon or pancreatic cancers. A change in the proportion of poor prognosis breast and uterine cancers suggests that some cancers that otherwise would have been diagnosed at an earlier stage will be detected in later years. Continued analysis of long-term trends is needed to understand the full impact of the pandemic on cancer incidence and outcomes

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes