Background: Many colorectal cancer (CRC)-related procedures were suspended during the COVID-19 pandemic. In this study, we predict the impact of resulting delays in screening (colonoscopy, FIT, sigmoidoscopy) and diagnosis on CRC outcomes, and compare different recovery scenarios. Methods: Using the MISCAN-Colon model, we simulated the US population and evaluated different impact and recovery scenarios. Scenarios were defined by the duration and severity of the disruption (% of eligible adults affected), the length of delays, and the duration of the recovery. During recovery (6, 12 or 24 months), capacity was increased to catch up missed procedures. Primary outcomes were excess CRC cases and deaths, and additional colonoscopies required during recovery. Results: With a 24-month recovery, the model predicted that the US population would develop 7,210 (0.18%) excess CRC cases during 2020-2040, and 6,950 (0.65%) excess CRC deaths, and require 108,500 (8.6%) additional colonoscopies per recovery month, compared to a no-disruption scenario. Shorter recovery periods of 6 and 12 months, respectively, decreased excess CRC deaths to 4,190 (0.39%) and 4,580 (0.43%), at the expense of 260,200-590,100 (20.7-47.0%) additional colonoscopies per month. Conclusions: The COVID-19 pandemic will likely cause more than 4,000 excess CRC deaths in the US, which could increase to more than 7,000 if recovery periods are longer. Impact: Our results highlight that catching-up CRC services within 12 months provides a good balance between required resources and mitigation of the impact of the disruption on CRC deaths.

Objectives Colorectal cancer (CRC) screening with a faecal immunochemical test (FIT) has been disrupted in many countries during the COVID-19 pandemic. Performing catch-up of missed screens while maintaining regular screening services requires additional colonoscopy capacity that may not be available. This study aimed to compare strategies that clear the screening backlog using limited colonoscopy resources. Methods A range of strategies were simulated using four country-specific CRC natural-history models: Adenoma and Serrated pathway to Colorectal CAncer (ASCCA) and MIcrosimulation SCreening ANalysis for CRC (MISCAN-Colon) (both in the Netherlands), Policy1-Bowel (Australia) and OncoSim (Canada). Strategies assumed a 3-month screening disruption with varying recovery period lengths (6, 12, and 24 months) and varying FIT thresholds for diagnostic colonoscopy. Increasing the FIT threshold reduces the number of referrals to diagnostic colonoscopy. Outcomes for each strategy were colonoscopy demand and excess CRC-related deaths due to the disruption. Results Performing catch-up using the regular FIT threshold in 6, 12 and 24 months could prevent most excess CRC-related deaths, but required 50%, 25% and 12.5% additional colonoscopy demand, respectively. Without exceeding usual colonoscopy demand, up to 60% of excess CRC-related deaths can be prevented by increasing the FIT threshold for 12 or 24 months. Large increases in FIT threshold could lead to additional deaths rather than preventing them. Conclusions Clearing the screening backlog in 24 months could avert most excess CRC-related deaths due to a 3-month disruption but would require a small increase in colonoscopy demand. Increasing the FIT threshold slightly over 24 months could ease the pressure on colonoscopy resources.

With all the information that is available on the World Wide Web, there is great demand for data mining techniques and sentiment analysis is a particularly popular domain, both in business and research. Sentiment analysis aims to determine the sentiment value, often on a positive-negative scale, for a given product or service based on a set of textual reviews. As fine-grained information is more useful than just a single overall score, modern aspect-based sentiment analysis techniques break down the sentiment and assign sentiment scores to various aspects of the product or service mentioned in the review. In this work, we focus on aspect-based sentiment analysis for complete reviews, as opposed to determining sentiment for aspects per sentence. Furthermore, we focus on semantic enrichment by employing ontology features in determining the sentiment value of a given pair of review and aspect. Next to that, we compare a pure review-level algorithm with aggregating the sentiment values of individual sentences. We show that the ontology features are important to correctly determine the sentiment of aspects and that the pure review-level algorithm outperforms the sentence aggregation method.

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in colorectal cancer (CRC) outcomes due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term CRC outcomes was measured by the number of life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3–18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in CRC outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

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