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      Age and Gender Variations in Cancer Diagnostic Intervals in 15 Cancers: Analysis of Data from the UK Clinical Practice Research Datalink

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          Abstract

          Background

          Time from symptomatic presentation to cancer diagnosis (diagnostic interval) is an important, and modifiable, part of the patient’s cancer pathway, and can be affected by various factors such as age, gender and type of presenting symptoms. The aim of this study was to quantify the relationships of diagnostic interval with these variables in 15 cancers diagnosed between 2007 and 2010 using routinely collected data from the Clinical Practice Research Datalink (CPRD) in the UK.

          Methods

          Symptom lists for each cancer were prepared from the literature and by consensus amongst the clinician researchers, which were then categorised into either NICE qualifying ( NICE) or not ( non-NICE) based on NICE Urgent Referral Guidelines for Suspected Cancer criteria. Multivariable linear regression models were fitted to examine the relationship between diagnostic interval (outcome) and the predictors: age, gender and symptom type.

          Results

          18,618 newly diagnosed cancer patients aged ≥40 who had a recorded symptom in the preceding year were included in the analysis. Mean diagnostic interval was greater for older patients in four disease sites (difference in days per 10 year increase in age; 95% CI): bladder (10.3; 5.5 to 15.1; P<0.001), kidney (11.0; 3.4 to 18.6; P=0.004), leukaemia (18.5; 8.8 to 28.1; P<0.001) and lung (10.1; 6.7 to 13.4; P<0.001). There was also evidence of longer diagnostic interval in older patients with colorectal cancer (P<0.001). However, we found that mean diagnostic interval was shorter with increasing age in two cancers: gastric (-5.9; -11.7 to -0.2; P=0.04) and pancreatic (-6.0; -11.2 to -0.7; P=0.03). Diagnostic interval was longer for females in six of the gender non-specific cancers (mean difference in days; 95% CI): bladder (12.2; 0.8 to 23.6; P=0.04), colorectal (10.4; 4.3 to 16.5; P=0.001), gastric (14.3; 1.1 to 27.6; P=0.03), head and neck (31.3; 6.2 to 56.5; P=0.02), lung (8.0; 1.2 to 14.9; P=0.02), and lymphoma (19.2; 3.8 to 34.7; P=0.01). Evidence of longer diagnostic interval was found for patients presenting with non-NICE symptoms in 10 of 15 cancers (mean difference in days; 95% CI): bladder (62.9; 48.7 to 77.2; P<0.001), breast (115.1; 105.9 to 124.3; P<0.001), cervical (60.3; 31.6 to 89.0; P<0.001), colorectal (25.8; 19.6 to 31.9; P<0.001), gastric (24.1; 3.4 to 44.8; P=0.02), kidney (22.1; 4.5 to 39.7; P=0.01), oesophageal (67.0; 42.1 to 92.0; P<0.001), pancreatic (48.6; 28.1 to 69.1; P<0.001), testicular (36.7; 17.0 to 56.4; P< 0.001), and endometrial (73.8; 60.3 to 87.3; P<0.001). Pooled analysis across all cancers demonstrated highly significant evidence of differences overall showing longer diagnostic intervals with increasing age (7.8 days; 6.4 to 9.1; P<0.001); for females (8.9 days; 5.5 to 12.2; P<0.001); and in non-NICE symptoms (27.7 days; 23.9 to 31.5; P<0.001).

          Conclusions

          We found age and gender-specific inequalities in time to diagnosis for some but not all cancer sites studied. Whilst these need further explanation, these findings can inform the development and evaluation of interventions intended to achieve timely diagnosis and improved cancer outcomes, such as to provide equity across all age and gender groupings.

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          Most cited references28

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          Validity of diagnostic coding within the General Practice Research Database: a systematic review.

          The UK-based General Practice Research Database (GPRD) is a valuable source of longitudinal primary care records and is increasingly used for epidemiological research. To conduct a systematic review of the literature on accuracy and completeness of diagnostic coding in the GPRD. Systematic review. Six electronic databases were searched using search terms relating to the GPRD, in association with terms synonymous with validity, accuracy, concordance, and recording. A positive predictive value was calculated for each diagnosis that considered a comparison with a gold standard. Studies were also considered that compared the GPRD with other databases and national statistics. A total of 49 papers are included in this review. Forty papers conducted validation of a clinical diagnosis in the GPRD. When assessed against a gold standard (validation using GP questionnaire, primary care medical records, or hospital correspondence), most of the diagnoses were accurately recorded in the patient electronic record. Acute conditions were not as well recorded, with positive predictive values lower than 50%. Twelve papers compared prevalence or consultation rates in the GPRD against other primary care databases or national statistics. Generally, there was good agreement between disease prevalence and consultation rates between the GPRD and other datasets; however, rates of diabetes and musculoskeletal conditions were underestimated in the GPRD. Most of the diagnoses coded in the GPRD are well recorded. Researchers using the GPRD may want to consider how well the disease of interest is recorded before planning research, and consider how to optimise the identification of clinical events.
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            Influence of delay on survival in patients with breast cancer: a systematic review.

            Most patients with breast cancer are detected after symptoms occur rather than through screening. The impact on survival of delays between the onset of symptoms and the start of treatment is controversial and cannot be studied in randomised controlled trials. We did a systematic review of observational studies (worldwide) of duration of symptoms and survival. We identified 87 studies (101,954 patients) with direct data linking delay (including delay by patients) and survival. We classified studies for analysis by type of data in the original reports: category I studies had actual 5-year survival data (38 studies, 53,912 patients); category II used actuarial or multivariate analyses (21 studies, 25,102 patients); and category III was all other types of data (28 studies, 22,940 patients). We tested the main hypothesis that longer delays would be associated with lower survival, and a secondary hypothesis that longer delays were associated with more advanced stage, which would account for lower survival. In category I studies, patients with delays of 3 months or more had 12% lower 5-year survival than those with shorter delays (odds ratio for death 1.47 [95% CI 1.42-1.53]) and those with delays of 3-6 months had 7% lower survival than those with shorter delays (1.24 [1.17-1.30]). In category II, 13 of 14 studies with unrestricted samples showed a significant adverse relation between longer delays and survival, whereas four of five studies of only patients with operable disease showed no significant relation. In category III, all three studies with unrestricted samples supported the primary hypothesis. The 13 informative studies showed that longer delays were associated with more advanced stage. In studies that controlled for stage, longer delay was not associated with shorter survival when the effect of stage on survival was taken into account. Delays of 3-6 months are associated with lower survival. These effects cannot be accounted for by lead-time bias. Efforts should be made to keep delays by patients and providers to a minimum.
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              Gender Differences in Determinants and Consequences of Health and Illness

              This paper uses a framework developed for gender and tropical diseases for the analysis of non-communicable diseases and conditions in developing and industrialized countries. The framework illustrates that gender interacts with the social, economic and biological determinants and consequences of tropical diseases to create different health outcomes for males and females. Whereas the framework was previously limited to developing countries where tropical infectious diseases are more prevalent, the present paper demonstrates that gender has an important effect on the determinants and consequences of health and illness in industrialized countries as well. This paper reviews a large number of studies on the interaction between gender and the determinants and consequences of chronic diseases and shows how these interactions result in different approaches to prevention, treatment, and coping with illness. Specific examples of chronic diseases are discussed in each section with respect to both developing and industrialized countries.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 May 2015
                2015
                : 10
                : 5
                : e0127717
                Affiliations
                [1 ]North Wales Centre for Primary Care Research, College of Health and Behavioural Sciences, Bangor University, Wrexham, United Kingdom
                [2 ]NIHR CLAHRC South West Peninsula, University of Exeter Medical School, Exeter, United Kingdom
                [3 ]School of Medicine, Pharmacy and Health, Wolfson Research Institute, Durham University, Durham, United Kingdom
                [4 ]University of Exeter Medical School, Exeter, United Kingdom
                [5 ]Institute of Primary Care & Public Health, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
                National Cancer Center, JAPAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: NUD RDN OCU. Performed the experiments: NUD OCU BC SS. Analyzed the data: NUD OCU BC. Contributed reagents/materials/analysis tools: GR WH RDN. Wrote the paper: NUD OCU GR WH BC SS RDN.

                Article
                PONE-D-14-39392
                10.1371/journal.pone.0127717
                4433335
                25978414
                bf5ac0f2-61e4-42bc-8b96-0ca17e27ef74
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 3 September 2014
                : 21 March 2015
                Page count
                Figures: 1, Tables: 5, Pages: 15
                Funding
                This research was funded by the National Cancer Action Team and the Department of Health Cancer Policy Team in England, UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views contained in it are those of the authors and do not represent those of the National Health Service (NHS), the National Institute for Health Research (NIHR) or the Department of Health policy (DoH) in England. OCU is supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) for the South West Peninsula at the Royal Devon and Exeter NHS Foundation Trust. RDN has received funding from both Betsi Cadwaladr University Health Board and Public Health Wales.
                Categories
                Research Article
                Custom metadata
                Interested researchers may contact CPRD directly to request third-party data. The data acquisition inquiries can be made at: kc@ 123456cprd.com and CPRD can be contacted in other ways as well at: The Clinical Practice Research Datalink Group, The Medicines and Healthcare products Regulatory Agency, 5th Floor, 151 Buckingham Palace Road, Victoria, London SW1W 9SZ General Enquiries: +44 (0)20 3080 6383. Fax: +44 (0)20 3118 9802. The authors have provided a detailed account of the dataset in the methods section of the paper and have provided the supplementary files for all the cancer diagnosis and symptom codes that were used to extract the data from CPRD's system so that interested readers may replicate the analysis presented in the present study. The authors obtained this third-party dataset from GPRD (now CPRD) by the Independent Scientific Advisory Committee under license numbers 09_0110 and 09_0111.

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