Predicting colorectal cancer risk from adenoma detection via a two-type branching process model.

Despite advances in the modeling and understanding of colorectal cancer development, the dynamics of the progression from benign adenomatous polyp to colorectal carcinoma are still not fully resolved. To take advantage of adenoma size and prevalence data in the National Endoscopic Database of the Clinical Outcomes Research Initiative (CORI) as well as colorectal cancer incidence and size data from the Surveillance Epidemiology and End Results (SEER) database, we construct a two-type branching process model with compartments representing adenoma and carcinoma cells. To perform parameter inference we present a new large-size approximation to the size distribution of the cancer compartment and validate our approach on simulated data. By fitting the model to the CORI and SEER data, we learn biologically relevant parameters, including the transition rate from adenoma to cancer. The inferred parameters allow us to predict the individualized risk of the presence of cancer cells for each screened patient. We provide a web application which allows the user to calculate these individual probabilities at https://ccrc-eth.shinyapps.io/CCRC/. For example, we find a 1 in 100 chance of cancer given the presence of an adenoma between 10 and 20mm size in an average risk patient at age 50. We show that our two-type branching process model recapitulates the early growth dynamics of colon adenomas and cancers and can recover epidemiological trends such as adenoma prevalence and cancer incidence while remaining mathematically and computationally tractable

Colorectal EMR outcomes in octogenarians versus younger patients referred for removal of large (≥20 mm) nonpedunculated polyps

Background and Aims Data are limited on safety and outcomes of colorectal EMR in octogenarians (≥80 years old). We sought to review outcome data for patients aged ≥80 in a prospectively collected database of patients referred for large polyp removal. Methods We retrospectively evaluated a database of patients referred for large (≥20 mm) nonpedunculated polyp removal. From 2000 to 2019, we compared the rates of follow-up, recurrence, adverse events, and synchronous neoplasia detection between younger patients and patients aged ≥80. Results There were 167 patients aged ≥80 years and 1686 <80 years. Patients in the elderly group returned for surveillance less often (67.1% vs 75.1%, P = .024), had greater first follow-up recurrence rates (27.5% vs 13.8%, P < .001), but had similar adverse event rates (1.8% vs 2.8%, P = .619) compared with younger patients. Rates of synchronous neoplasia were similar and high in both groups. Conclusions EMR is safe and well tolerated for large polyp removal in patients over 80 years old. Patients aged ≥80 years are less likely to present for follow-up after EMR. They had a higher recurrence rate and a similarly high prevalence of synchronous precancerous lesions. Follow-up after EMR should be encouraged in the elderly, and an attempt to clear the colon of synchronous disease at the time of the initial EMR may be warranted

Predicting colorectal cancer risk from adenoma detection via a two-type branching process model

Despite advances in the modeling and understanding of colorectal cancer development, the dynamics of the progression from benign adenomatous polyp to colorectal carcinoma are still not fully resolved. To take advantage of adenoma size and prevalence data in the National Endoscopic Database of the Clinical Outcomes Research Initiative (CORI) as well as colorectal cancer incidence and size data from the Surveillance Epidemiology and End Results (SEER) database, we construct a two-type branching process model with compartments representing adenoma and carcinoma cells. To perform parameter inference we present a new large-size approximation to the size distribution of the cancer compartment and validate our approach on simulated data. By fitting the model to the CORI and SEER data, we learn biologically relevant parameters, including the transition rate from adenoma to cancer. The inferred parameters allow us to predict the individualized risk of the presence of cancer cells for each screened patient. We provide a web application which allows the user to calculate these individual probabilities at https://ccrc-eth.shinyapps.io/CCRC/. For example, we find a 1 in 100 chance of cancer given the presence of an adenoma between 10 and 20mm size in an average risk patient at age 50. We show that our two-type branching process model recapitulates the early growth dynamics of colon adenomas and cancers and can recover epidemiological trends such as adenoma prevalence and cancer incidence while remaining mathematically and computationally tractable

Predicting colorectal cancer risk from adenoma detection via a two-type branching process model

Despite advances in the modeling and understanding of colorectal cancer development, the dynamics of the progression from benign adenomatous polyp to colorectal carcinoma are still not fully resolved. To take advantage of adenoma size and prevalence data in the National Endoscopic Database of the Clinical Outcomes Research Initiative (CORI) as well as colorectal cancer incidence and size data from the Surveillance Epidemiology and End Results (SEER) database, we construct a two-type branching process model with compartments representing adenoma and carcinoma cells. To perform parameter inference we present a new large-size approximation to the size distribution of the cancer compartment and validate our approach on simulated data. By fitting the model to the CORI and SEER data, we learn biologically relevant parameters, including the transition rate from adenoma to cancer. The inferred parameters allow us to predict the individualized risk of the presence of cancer cells for each screened patient. We provide a web application which allows the user to calculate these individual probabilities at https://ccrc-eth.shinyapps.io/CCRC/. For example, we find a 1 in 100 chance of cancer given the presence of an adenoma between 10 and 20mm size in an average risk patient at age 50. We show that our two-type branching process model recapitulates the early growth dynamics of colon adenomas and cancers and can recover epidemiological trends such as adenoma prevalence and cancer incidence while remaining mathematically and computationally tractable.ISSN:1553-734XISSN:1553-735