The COVID-19 pandemic created a backlog in colorectal cancer (CRC) screening and surveillance colonoscopies. The real impact in Argentina is not fully known.

To estimate the impact of the COVID-19 pandemic on CRC prevention by comparing the number of CRC screening and surveillance consults in a clinical decision support-tool used in Argentina before, during and after pandemic lockdown.

We analyzed data from May 2019 to December 2021 from CaPtyVa, a clinical decision support tool for CRC screening and surveillance. Queries were divided in pre-pandemic (May 2019 to March 2020), lockdown (April 2020 to December 2020), and post-lockdown (January 2021 to December 2021). The number of CRC monthly screening and surveillance visits were compared among the three periods and stratified according to CRC risk.

Overall, 27,563 consults were analyzed of which 9035 were screening and 18,528 were surveillance. Pre-pandemic, the median number of screening consults was 346 per month (IQR25-75 280-410). There was a decrease to 156 (80-210)/month (p<0.005) during lockdown that partially recovered during post-lockdown to 230 (170-290)/month (p=0.05). Pre-pandemic, the median number of surveillance consults was 716 (560-880)/month. They decreased to 354 (190-470)/month during lockdown (p<.05) and unlike screening, completely recovered during post-lockdown to 581 (450-790)/month.

There was a >50% decrease in the number of CRC screening and surveillance consults registered in CaPtyVa during lockdown in Argentina. Post-lockdown, surveillance consults recovered to pre-pandemic levels, but screening consults remained at 66% of pre-pandemic levels. This has implications for delays in CRC diagnoses and patient outcomes.

Around the world, cancer care services are facing many operational challenges. Operations management research can provide important solutions to these challenges, from screening and diagnosis to treatment. In recent years, the growth in the number of papers published on cancer care operations management (CCOM) indicates that development has been fast. Within this context, the objective of this research was to understand the evolution of CCOM through a comprehensive study and an up-to-date bibliometric analysis of the literature. To achieve this aim, the Web of Science Core Collection database was used as the source of bibliographic records. The data-mining and quantitative tools in the software Biblioshiny were used to analyze CCOM articles published from 2010 to 2021. First, a historical analysis described CCOM research, the sources, and the subfields. Second, an analysis of keywords highlighted the significant developments in this field. Third, an analysis of research themes identified three main directions for future research in CCOM, which has 11 evolutionary paths. Finally, this paper discussed the gaps in CCOM research and the areas that require further investigation and development.

Colorectal carcinoma screening programs have shown success in lowering both the incidence and mortality rate of colorectal carcinoma at a population level, in part because this carcinoma is relatively slow growing and has an identifiable premalignant lesion. Still, many patients do not undergo the recommended screening for colorectal carcinoma, and of those who do, a subset may be over- or under-diagnosed by the currently available testing methods. The primary purpose of this article is to review the data regarding currently available colorectal cancer screening modalities, which include fecal occult blood testing, direct colonic visualization, and noninvasive imaging techniques. In addition, readers will be introduced to a variety of biomarkers that may serve as stand-alone or adjunct tests in the future. Finally, there is a brief discussion of the current epidemiologic considerations that public health officials must address as they create population screening guidelines. The data we provide as laboratory physicians and scientists are critical to the construction of appropriate recommendations that ultimately decrease the burden of disease from colorectal carcinoma.

A systematic review and meta-analysis was performed to summarize the available evidence on risk scores for predicting advanced colorectal neoplasia (advanced adenomas and cancer) in average-risk and asymptomatic populations undergoing screening colonoscopy.

PubMed, EMBASE, and Web of Science databases were searched up to 28 March 2018. Studies that developed or validated a risk score to predict the risk of advanced colorectal neoplasia were included. Two reviewers independently extracted study characteristics including diagnostic performance indicators and assessed risk of bias and applicability in the included studies. Meta-analyses were conducted to determine the overall discrimination of risk scores evaluated by more than 1 study.

A total of 22 studies including 17 original risk scores were identified. Risk scores included a median number of 5 risk factors. Factors most commonly included were age, sex, family history in first-degree relatives, body mass index and smoking. The area under the receiver operating characteristic curve of risk scores ranged from 0.62 to 0.77 in the individual studies and from 0.61 to 0.70 in the meta-analyses.

Although the majority of available risk scores had relatively weak discriminatory power, they may be of some use for risk stratification in CRC screening. Rather than developing more risk scores based on environmental risk factors, future research should focus on exploring possibilities of enhancing predictive power by combining risk factor data with novel laboratory matters, such as polygenetic risk scores.

Decision models representing the clinical situations where treatment options entail a significant risk of morbidity or mortality should consider the variations in risk preferences of individuals. In this study, we develop a stochastic modeling framework that optimizes risk-sensitive diagnostic decisions after a mammography exam. For a given patient, our objective is to find the utility maximizing diagnostic decisions where we define the utility over quality-adjusted survival duration. We use real data from a private mammography database to numerically solve our model for various utility functions. Our choice of utility functions for the numerical analysis is driven by actual patient behavior encountered in clinical practice. We find that invasive diagnostic procedures such as biopsies are more aggressively used than what the optimal risk-neutral policy would suggest, implying a far-sighted (or equivalently risk-seeking) behavior. When risk preferences are incorporated into the clinical practice, policy makers should bear in mind that a welfare loss in terms of survival duration is inevitable as evidenced by our structural and empirical results.