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Giannakou K, Lamnisos D. Small-Area Geographic and Socioeconomic Inequalities in Colorectal Cancer in Cyprus. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:341. [PMID: 36612661 PMCID: PMC9819875 DOI: 10.3390/ijerph20010341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 12/15/2022] [Indexed: 06/17/2023]
Abstract
Colorectal cancer (CRC) is one of the leading causes of death and morbidity worldwide. To date, the relationship between regional deprivation and CRC incidence or mortality has not been studied in the population of Cyprus. The objective of this study was to analyse the geographical variation of CRC incidence and mortality and its possible association with socioeconomic inequalities in Cyprus for the time period of 2000-2015. This is a small-area ecological study in Cyprus, with census tracts as units of spatial analysis. The incidence date, sex, age, postcode, primary site, death date in case of death, or last contact date of all alive CRC cases from 2000-2015 were obtained from the Cyprus Ministry of Health's Health Monitoring Unit. Indirect standardisation was used to calculate the sex and age Standardise Incidence Ratios (SIRs) and Standardised Mortality Ratios (SMRs) of CRC while the smoothed values of SIRs, SMRs, and Mortality to Incidence ratio (M/I ratio) were estimated using the univariate Bayesian Poisson log-linear spatial model. To evaluate the association of CRC incidence and mortality rate with socioeconomic deprivation, we included the national socioeconomic deprivation index as a covariate variable entering in the model either as a continuous variable or as a categorical variable representing quartiles of areas with increasing levels of socioeconomic deprivation. The results showed that there are geographical areas having 15% higher SIR and SMR, with most of those areas located on the east coast of the island. We found higher M/I ratio values in the rural, remote, and less dense areas of the island, while lower rates were observed in the metropolitan areas. We also discovered an inverted U-shape pattern in CRC incidence and mortality with higher rates in the areas classified in the second quartile (Q2-areas) of the socioeconomic deprivation index and lower rates in rural, remote, and less dense areas (Q4-areas). These findings provide useful information at local and national levels and inform decisions about resource allocation to geographically targeted prevention and control plans to increase CRC screening and management.
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Alsadhan N, Almaiman A, Pujades-Rodriguez M, Brennan C, Shuweihdi F, Alhurishi SA, West RM. A systematic review of methods to estimate colorectal cancer incidence using population-based cancer registries. BMC Med Res Methodol 2022; 22:144. [PMID: 35590277 PMCID: PMC9118801 DOI: 10.1186/s12874-022-01632-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/04/2022] [Indexed: 11/14/2022] Open
Abstract
Background Epidemiological studies of incidence play an essential role in quantifying disease burden, resource planning, and informing public health policies. A variety of measures for estimating cancer incidence have been used. Appropriate reporting of incidence calculations is essential to enable clear interpretation. This review uses colorectal cancer (CRC) as an exemplar to summarize and describe variation in commonly employed incidence measures and evaluate the quality of reporting incidence methods. Methods We searched four databases for CRC incidence studies published between January 2010 and May 2020. Two independent reviewers screened all titles and abstracts. Eligible studies were population-based cancer registry studies evaluating CRC incidence. We extracted data on study characteristics and author-defined criteria for assessing the quality of reporting incidence. We used descriptive statistics to summarize the information. Results This review retrieved 165 relevant articles. The age-standardized incidence rate (ASR) (80%) was the most commonly reported incidence measure, and the 2000 U.S. standard population the most commonly used reference population (39%). Slightly more than half (54%) of the studies reported CRC incidence stratified by anatomical site. The quality of reporting incidence methods was suboptimal. Of all included studies: 45 (27%) failed to report the classification system used to define CRC; 63 (38%) did not report CRC codes; and only 20 (12%) documented excluding certain CRC cases from the numerator. Concerning the denominator estimation: 61% of studies failed to state the source of population data; 24 (15%) indicated census years; 10 (6%) reported the method used to estimate yearly population counts; and only 5 (3%) explicitly explained the population size estimation procedure to calculate the overall average incidence rate. Thirty-three (20%) studies reported the confidence interval for incidence, and only 7 (4%) documented methods for dealing with missing data. Conclusion This review identified variations in incidence calculation and inadequate reporting of methods. We outlined recommendations to optimize incidence estimation and reporting practices. There is a need to establish clear guidelines for incidence reporting to facilitate assessment of the validity and interpretation of reported incidence. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-022-01632-7.
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Affiliation(s)
- Norah Alsadhan
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia. .,School of Medicine, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK.
| | - Alaa Almaiman
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Mar Pujades-Rodriguez
- School of Medicine, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Cathy Brennan
- School of Medicine, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Farag Shuweihdi
- School of Medicine, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Sultana A Alhurishi
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Robert M West
- School of Medicine, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
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Raginel T, Grandazzi G, Launoy G, Trocmé M, Christophe V, Berchi C, Guittet L. Social inequalities in cervical cancer screening: a discrete choice experiment among French general practitioners and gynaecologists. BMC Health Serv Res 2020; 20:693. [PMID: 32718319 PMCID: PMC7385880 DOI: 10.1186/s12913-020-05479-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 06/28/2020] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Cervical cancer screening is effective in reducing mortality due to uterine cervical cancer (UCC). However, inequalities in participation in UCC screening exist, especially according to age and social status. Considering the current situation in France regarding the ongoing organized UCC screening campaign, we aimed to assess general practitioners' (GPs) and gynaecologists' preferences for actions designed to reduce screening inequalities. METHODS French physicians' preferences to UCC screening modalities was assessed using a discrete choice experiment. A national cross-sectional questionnaire was sent between September and October 2014 to 500 randomly selected physicians, and numerically to all targeted physicians working in the French region Midi-Pyrénées. Practitioners were offered 11 binary choices of organized screening scenarios in order to reduce inequalities in UCC screening participation. Each scenario was based on five attributes corresponding to five ways to enhance participation in UCC screening while reducing screening inequalities. RESULTS Among the 123 respondents included, practitioners voted for additional interventions targeting non-screened women overall (p < 0.05), including centralized invitations sent from a central authority and involving the mentioned attending physician, or providing attending physicians with the lists of unscreened women among their patients. However, they rejected the specific targeting of women over 50 years old (p < 0.01) or living in deprived areas (p < 0.05). Only GPs were in favour of allowing nurses to perform Pap smears, but both GPs and gynaecologists rejected self-collected oncogenic papillomavirus testing. CONCLUSIONS French practitioners tended to value the traditional principle of universalism. As well as rejecting self-collected oncogenic papillomavirus testing, their reluctance to support the principle of proportionate universalism relying on additional interventions addressing differences in socioeconomic status needs further evaluation. As these two concepts have already been recommended as secondary development leads for the French national organized screening campaign currently being implemented, the adherence of practitioners and the adaptation of these concepts are necessary conditions for reducing inequalities in health care.
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Affiliation(s)
- Thibaut Raginel
- NORMANDIE UNIV, UNICAEN, INSERM, ANTICIPE, 14000 Caen, France
- NORMANDIE UNIV, UNICAEN, UFR Sante, Department of General Practice, 14000 Caen, France
| | | | - Guy Launoy
- NORMANDIE UNIV, UNICAEN, INSERM, ANTICIPE, 14000 Caen, France
| | - Mélanie Trocmé
- Univ. Lille, UMR 9193 - SCALab - Sciences Cognitives et Sciences Affectives, F-59000 Lille, France
| | - Véronique Christophe
- Univ. Lille, UMR 9193 - SCALab - Sciences Cognitives et Sciences Affectives, F-59000 Lille, France
| | - Célia Berchi
- NORMANDIE UNIV, UNICAEN, INSERM, ANTICIPE, 14000 Caen, France
| | - Lydia Guittet
- NORMANDIE UNIV, UNICAEN, INSERM, ANTICIPE, 14000 Caen, France
- Caen University Hospital, Département d’Information Médicale, Avenue de la Côte de Nacre, 14033 Caen, France
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Tian Y, Li J, Zhou T, Tong D, Chi S, Kong X, Ding K, Li J. Spatially varying effects of predictors for the survival prediction of nonmetastatic colorectal Cancer. BMC Cancer 2018; 18:1084. [PMID: 30409119 PMCID: PMC6225720 DOI: 10.1186/s12885-018-4985-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 10/23/2018] [Indexed: 12/19/2022] Open
Abstract
Background An increasing number of studies have identified spatial differences in colorectal cancer survival. However, little is known about the spatially varying effects of predictors in survival prediction modeling studies of colorectal cancer that have focused on estimating the absolute survival risk for patients from a wide range of populations. This study aimed to demonstrate the spatially varying effects of predictors of survival for nonmetastatic colorectal cancer patients. Methods Patients diagnosed with nonmetastatic colorectal cancer from 2004 to 2013 who were followed up through the end of 2013 were extracted from the Surveillance Epidemiology End Results registry (Patients: 128061). The log-rank test and the restricted mean survival time were used to evaluate survival outcome differences among spatial clusters corresponding to a widely used clinical predictor: stage determined by AJCC 7th edition staging system. The heterogeneity test, which is used in meta-analyses, revealed the spatially varying effects of single predictors. Then, considering the above predictors in a standard survival prediction model based on spatially clustered data, the spatially varying coefficients of these models revealed that some covariate effects may not be constant across the geographic regions of the study. Then, two types of survival prediction models (a statistical model and a machine learning model) were built; these models considered the predictors and enabled survival prediction for patients from a wide range of geographic regions. Results Based on univariate and multivariate analysis, some prognostic factors, such as “TNM stage”, “tumor size” and “age at diagnosis,” have significant spatially varying effects among different regions. When considering these spatially varying effects, machine learning models have fewer assumption constraints (such as proportional hazard assumptions) and better predictive performance compared with statistical models. Upon comparing the concordance indexes of these two models, the machine learning model was found to be more accurate (0.898[0.895,0.902]) than the statistical model (0.732 [0.726, 0.738]). Conclusions Based on this study, it’s recommended that the spatially varying effect of predictors should be considered when building survival prediction models involving large-scale and multicenter research data. Machine learning models that are not limited by the requirement of a statistical hypothesis are promising alternative models. Electronic supplementary material The online version of this article (10.1186/s12885-018-4985-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yu Tian
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou, 310027, Zhejiang Province, China
| | - Jun Li
- Department of Surgical Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, 31009, Zhejiang Province, China
| | - Tianshu Zhou
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou, 310027, Zhejiang Province, China.
| | - Danyang Tong
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou, 310027, Zhejiang Province, China
| | - Shengqiang Chi
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou, 310027, Zhejiang Province, China
| | - Xiangxing Kong
- Department of Surgical Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, 31009, Zhejiang Province, China
| | - Kefeng Ding
- Department of Surgical Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, 31009, Zhejiang Province, China
| | - Jingsong Li
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou, 310027, Zhejiang Province, China
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