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Virginie MLIL, Zhao Q, Liu L. African colorectal cancer burden in 2022 and projections to 2050. Ecancermedicalscience 2024; 18:1780. [PMID: 39430071 PMCID: PMC11489094 DOI: 10.3332/ecancer.2024.1780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Indexed: 10/22/2024] Open
Abstract
Introduction The burden of colorectal cancer (CRC) is on a rapid increase on the African continent, yet grossly under reported. Herein, we provide and updated estimates of CRC burden (incidence and mortality) across Africa as of 2022, and make crucial predictions to 2050. Methods We gathered information on CRC incidence and mortality from the GLOBOCAN 2022 database, which covers 185 countries. The age-standardised incidence and mortality rates (ASRs) per 100,000 person-years were determined. Cases and deaths up to 2050 were estimated using 2022 incidence and mortality rates. Results In 2022, an estimated 70,428 cases and 46,087 mortalities due to CRC were recorded across the African continent. Africa's ASRs for CRC incidence and mortality were 8.2 and 5.6 per 100,000 population, respectively, and were highest in North Africa followed by East Africa. At national levels, CRC ranked in the top four of the most commonly diagnosed cancers in more than half (56%) of African countries. ASRs of both incidence and mortality were higher among males than females. New cases are predicted to increase by 139.7% (from 70,428 in 2022 to 168,683 in 2050) at the current incidence rate. Similarly, mortalities will increase by 155.2% (from 46,061 in 2022 to 117,568 in 2050). Conclusion CRC remains a major cause of morbidity and mortality in many African countries, and the number of new cases and deaths is predicted to rise significantly by 2050. Efforts to reduce the incidence of preventable CRC cases should be prioritised.
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Affiliation(s)
| | - Qiu Zhao
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Hubei Clinical Center & Key Laboratory of Intestinal and Colorectal Disease, Wuhan 430071, China
| | - Lan Liu
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
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Juul FE, Cross AJ, Schoen RE, Senore C, Pinsky PF, Miller EA, Segnan N, Wooldrage K, Wieszczy-Szczepanik P, Armaroli P, Garborg KK, Adami HO, Hoff G, Kalager M, Bretthauer M, Holme Ø, Løberg M. Effectiveness of Colonoscopy Screening vs Sigmoidoscopy Screening in Colorectal Cancer. JAMA Netw Open 2024; 7:e240007. [PMID: 38421651 PMCID: PMC10905314 DOI: 10.1001/jamanetworkopen.2024.0007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 01/02/2024] [Indexed: 03/02/2024] Open
Abstract
Importance Randomized clinical screening trials have shown that sigmoidoscopy screening reduces colorectal cancer (CRC) incidence and mortality. Colonoscopy has largely replaced sigmoidoscopy for CRC screening, but long-term results from randomized trials on colonoscopy screening are still lacking. Objective To estimate the additional screening benefit of colonoscopy compared with sigmoidoscopy. Design, Setting, and Participants This comparative effectiveness simulation study pooled data on 358 204 men and women randomly assigned to sigmoidoscopy screening or usual care in 4 randomized sigmoidoscopy screening trials conducted in Norway, Italy, the US, and UK with inclusion periods in the years 1993 to 2001. The primary analysis of the study was conducted from January 19 to December 30, 2021. Intervention Invitation to endoscopic screening. Main Outcomes and Measures Primary outcomes were CRC incidence and mortality. Using pooled 15-year follow-up data, colonoscopy screening effectiveness was estimated assuming that the efficacy of colonoscopy in the proximal colon was similar to that observed in the distal colon in the sigmoidoscopy screening trials. The simulation model was validated using data from Norwegian participants in a colonoscopy screening trial. Results This analysis included 358 204 individuals (181 971 women [51%]) aged 55 to 64 years at inclusion with a median follow-up time ranging from 15 to 17 years. Compared with usual care, colonoscopy prevented an estimated 50 (95% CI, 42-58) CRC cases per 100 000 person-years, corresponding to 30% incidence reduction (rate ratio, 0.70 [95% CI, 0.66-0.75]), and prevented an estimated 15 (95% CI, 11-19) CRC deaths per 100 000 person-years, corresponding to 32% mortality reduction (rate ratio, 0.68 [95% CI, 0.61-0.76]). The additional benefit of colonoscopy screening compared with sigmoidoscopy was 12 (95% CI, 10-14) fewer CRC cases and 4 (95% CI, 3-5) fewer CRC deaths per 100 000 person-years, corresponding to percentage point reductions of 6.9 (95% CI, 6.0-7.9) for CRC incidence and 7.6 (95% CI, 5.7-9.6) for CRC mortality. The number needed to switch from sigmoidoscopy to colonoscopy screening was 560 (95% CI, 486-661) to prevent 1 CRC case and 1611 (95% CI, 1275-2188) to prevent 1 CRC death. Conclusions and Relevance The findings of this comparative effectiveness study assessing long-term follow-up after CRC screening suggest that there was an additional preventive effect on CRC incidence and mortality associated with colonoscopy screening compared with sigmoidoscopy screening, but the additional preventive effect was less than what was achieved by introducing sigmoidoscopy screening where no screening existed. The results probably represent the upper limit of what may be achieved with colonoscopy screening compared with sigmoidoscopy screening.
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Affiliation(s)
- Frederik E Juul
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
| | - Amanda J Cross
- Cancer Screening & Prevention Research Group, Department of Surgery & Cancer, Imperial College London, London, United Kingdom
| | - Robert E Schoen
- Division of Gastroenterology, Hepatology and Nutrition, Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Carlo Senore
- University Hospital Città della Salute e della Scienza, Turin, Italy
| | - Paul F Pinsky
- Division of Cancer Prevention, National Cancer Institute, Rockville, Maryland
| | - Eric A Miller
- Division of Cancer Prevention, National Cancer Institute, Rockville, Maryland
| | - Nereo Segnan
- University Hospital Città della Salute e della Scienza, Turin, Italy
| | - Kate Wooldrage
- Cancer Screening & Prevention Research Group, Department of Surgery & Cancer, Imperial College London, London, United Kingdom
| | - Paulina Wieszczy-Szczepanik
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Paola Armaroli
- University Hospital Città della Salute e della Scienza, Turin, Italy
| | - Kjetil K Garborg
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
| | - Hans-Olov Adami
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Geir Hoff
- Section for Colorectal Cancer Screening, Cancer Registry of Norway, Oslo, Norway
- Department of Research and Development, Telemark Hospital Trust, Skien, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Mette Kalager
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
| | - Michael Bretthauer
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
| | - Øyvind Holme
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
- Department of Medicine, Sorlandet Hospital Health Trust, Kristiansand, Norway
| | - Magnus Løberg
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Clinical Effectiveness Research Group, Oslo University Hospital, Oslo, Norway
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Lang BM, Kuipers J, Misselwitz B, Beerenwinkel N. Predicting colorectal cancer risk from adenoma detection via a two-type branching process model. PLoS Comput Biol 2020; 16:e1007552. [PMID: 32023238 PMCID: PMC7001909 DOI: 10.1371/journal.pcbi.1007552] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 11/18/2019] [Indexed: 12/31/2022] Open
Abstract
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 cancer is a major public health burden. The development of colorectal cancer starts with the mutational initiation of non-cancerous growths in the form of benign adenomatous polyps. These adenomas grow over time with the potential to develop into carcinomas. Many mathematical and simulation-based models have been used to gain insight into this process. We aimed to understand rates of adenoma growth and transition into carcinomas, to enable better planning of colorectal cancer screening strategies. To this end, we expand the two-type branching process model, and fit it on data describing the frequency of sizes of adenomas and carcinomas. The results provide new, data-based, estimates of the rates of development for colorectal cancer.
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Affiliation(s)
- Brian M. Lang
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Jack Kuipers
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Benjamin Misselwitz
- Department of Visceral Surgery and Medicine, Inselspital Bern and Bern University, Bern, Switzerland
- Department of Gastroenterology and Hepatology, University Hospital Zurich and Zurich University, Zurich, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- * E-mail:
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Jeon J, Du M, Schoen RE, Hoffmeister M, Newcomb PA, Berndt SI, Caan B, Campbell PT, Chan AT, Chang-Claude J, Giles GG, Gong J, Harrison TA, Huyghe JR, Jacobs EJ, Li L, Lin Y, Le Marchand L, Potter JD, Qu C, Bien SA, Zubair N, Macinnis RJ, Buchanan DD, Hopper JL, Cao Y, Nishihara R, Rennert G, Slattery ML, Thomas DC, Woods MO, Prentice RL, Gruber SB, Zheng Y, Brenner H, Hayes RB, White E, Peters U, Hsu L. Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors. Gastroenterology 2018; 154:2152-2164.e19. [PMID: 29458155 PMCID: PMC5985207 DOI: 10.1053/j.gastro.2018.02.021] [Citation(s) in RCA: 215] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2017] [Revised: 01/22/2018] [Accepted: 02/06/2018] [Indexed: 02/06/2023]
Abstract
BACKGROUND & AIMS Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening. METHODS We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry. RESULTS In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62-0.64) for men and 0.62 (95% confidence interval, 0.61-0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk. CONCLUSIONS We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.
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Affiliation(s)
- Jihyoun Jeon
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan.
| | - Mengmeng Du
- Memorial Sloan Kettering, New York, New York
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg, Germany; German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Bette Caan
- Division of Research, Kaiser Permanente Medical Care Program, Oakland, California
| | - Peter T Campbell
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Jenny Chang-Claude
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg, Germany; German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Graham G Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, and Centre for Epidemiology and Biostatistics, School of Global and Population Health, University of Melbourne, Melbourne, Australia
| | - Jian Gong
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Tabitha A Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Eric J Jacobs
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia
| | - Li Li
- Case Western Reserve University, Cleveland, Ohio
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - John D Potter
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Stephanie A Bien
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Niha Zubair
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Robert J Macinnis
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, and Centre for Epidemiology and Biostatistics, School of Global and Population Health, University of Melbourne, Melbourne, Australia
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia; Genetic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia; Department of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Yin Cao
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Reiko Nishihara
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | | | - Martha L Slattery
- Department of Internal Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah
| | - Duncan C Thomas
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Michael O Woods
- Memorial University of Newfoundland, St John's, Newfoundland, Canada
| | - Ross L Prentice
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Stephen B Gruber
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California
| | - Yingye Zheng
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg, Germany; German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Richard B Hayes
- Division of Epidemiology, Department of Population Health, New York University School of Medicine, New York, New York
| | - Emily White
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
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