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      Cancer risk in individuals with major birth defects: large Nordic population based case-control study among children, adolescents, and adults

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          Abstract

          Objective

          To examine associations between birth defects and cancer from birth into adulthood.

          Design

          Population based nested case-control study.

          Setting

          Nationwide health registries in Denmark, Finland, Norway, and Sweden.

          Participants

          62 295 cancer cases (0-46 years) and 724 542 frequency matched controls (matched on country and birth year), born between 1967 and 2014.

          Main outcome measures

          Relative risk of cancer in relation to major birth defects, estimated as odds ratios with 99% confidence intervals from logistic regression models.

          Results

          Altogether, 3.5% (2160/62 295) of cases and 2.2% (15 826/724 542) of controls were born with major birth defects. The odds ratio of cancer for people with major birth defects compared with those without was 1.74 (99% confidence interval 1.63 to 1.84). For individuals with non-chromosomal birth defects, the odds ratio of cancer was 1.54 (1.44 to 1.64); for those with chromosomal anomalies, the odds ratio was 5.53 (4.67 to 6.54). Many structural birth defects were associated with later cancer in the same organ system or anatomical location, such as defects of the eye, nervous system, and urinary organs. The odds ratio of cancer increased with number of defects and decreased with age, for both non-chromosomal and chromosomal anomalies. The odds ratio of cancer in people with any non-chromosomal birth defect was lower in adults (≥20 years: 1.21, 1.09 to 1.33) than in adolescents (15-19 years: 1.58, 1.31 to 1.90) and children (0-14 years: 2.03, 1.85 to 2.23). The relative overall cancer risk among adults with chromosomal anomalies was markedly reduced from 11.3 (9.35 to 13.8) in children to 1.50 (1.01 to 2.24). Among adults, skeletal dysplasia (odds ratio 3.54, 1.54 to 8.15), nervous system defects (1.76, 1.16 to 2.65), chromosomal anomalies (1.50, 1.01 to 2.24), genital organs defects (1.43, 1.14 to 1.78), and congenital heart defects (1.28, 1.02 to 1.59) were associated with overall cancer risk.

          Conclusions

          The increased risk of cancer in individuals with birth defects persisted into adulthood, both for non-chromosomal and chromosomal anomalies. Further studies on the molecular mechanisms involved are warranted.

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          Most cited references33

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          External review and validation of the Swedish national inpatient register

          Background The Swedish National Inpatient Register (IPR), also called the Hospital Discharge Register, is a principal source of data for numerous research projects. The IPR is part of the National Patient Register. The Swedish IPR was launched in 1964 (psychiatric diagnoses from 1973) but complete coverage did not begin until 1987. Currently, more than 99% of all somatic (including surgery) and psychiatric hospital discharges are registered in the IPR. A previous validation of the IPR by the National Board of Health and Welfare showed that 85-95% of all diagnoses in the IPR are valid. The current paper describes the history, structure, coverage and quality of the Swedish IPR. Methods and results In January 2010, we searched the medical databases, Medline and HighWire, using the search algorithm "validat* (inpatient or hospital discharge) Sweden". We also contacted 218 members of the Swedish Society of Epidemiology and an additional 201 medical researchers to identify papers that had validated the IPR. In total, 132 papers were reviewed. The positive predictive value (PPV) was found to differ between diagnoses in the IPR, but is generally 85-95%. Conclusions In conclusion, the validity of the Swedish IPR is high for many but not all diagnoses. The long follow-up makes the register particularly suitable for large-scale population-based research, but for certain research areas the use of other health registers, such as the Swedish Cancer Register, may be more suitable.
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            The Danish National Patient Registry: a review of content, data quality, and research potential

            Background The Danish National Patient Registry (DNPR) is one of the world’s oldest nationwide hospital registries and is used extensively for research. Many studies have validated algorithms for identifying health events in the DNPR, but the reports are fragmented and no overview exists. Objectives To review the content, data quality, and research potential of the DNPR. Methods We examined the setting, history, aims, content, and classification systems of the DNPR. We searched PubMed and the Danish Medical Journal to create a bibliography of validation studies. We included also studies that were referenced in retrieved papers or known to us beforehand. Methodological considerations related to DNPR data were reviewed. Results During 1977–2012, the DNPR registered 8,085,603 persons, accounting for 7,268,857 inpatient, 5,953,405 outpatient, and 5,097,300 emergency department contacts. The DNPR provides nationwide longitudinal registration of detailed administrative and clinical data. It has recorded information on all patients discharged from Danish nonpsychiatric hospitals since 1977 and on psychiatric inpatients and emergency department and outpatient specialty clinic contacts since 1995. For each patient contact, one primary and optional secondary diagnoses are recorded according to the International Classification of Diseases. The DNPR provides a data source to identify diseases, examinations, certain in-hospital medical treatments, and surgical procedures. Long-term temporal trends in hospitalization and treatment rates can be studied. The positive predictive values of diseases and treatments vary widely (<15%–100%). The DNPR data are linkable at the patient level with data from other Danish administrative registries, clinical registries, randomized controlled trials, population surveys, and epidemiologic field studies – enabling researchers to reconstruct individual life and health trajectories for an entire population. Conclusion The DNPR is a valuable tool for epidemiological research. However, both its strengths and limitations must be considered when interpreting research results, and continuous validation of its clinical data is essential.
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              Analysis of matched case-control studies

              There are two common misconceptions about case-control studies: that matching in itself eliminates (controls) confounding by the matching factors, and that if matching has been performed, then a “matched analysis” is required. However, matching in a case-control study does not control for confounding by the matching factors; in fact it can introduce confounding by the matching factors even when it did not exist in the source population. Thus, a matched design may require controlling for the matching factors in the analysis. However, it is not the case that a matched design requires a matched analysis. Provided that there are no problems of sparse data, control for the matching factors can be obtained, with no loss of validity and a possible increase in precision, using a “standard” (unconditional) analysis, and a “matched” (conditional) analysis may not be required or appropriate.
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                Author and article information

                Contributors
                Role: doctoral student
                Role: professor
                Role: professor
                Role: professor
                Role: professor
                Role: associate professor
                Role: senior consultant
                Role: adjunct professor
                Role: clinical specialist
                Role: postdoctoral fellow
                Role: professor
                Role: epidemiologist
                Role: professor
                Journal
                BMJ
                BMJ
                BMJ-UK
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2020
                02 December 2020
                : 371
                : m4060
                Affiliations
                [1 ]Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
                [2 ]Division of Mental and Physical Health, Norwegian Institute of Public Health, Bergen, Norway
                [3 ]Unit of Clinical Epidemiology, Department of Medicine/Solna, Karolinska Institute, Stockholm, Sweden
                [4 ]Information Services Department, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
                [5 ]Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
                [6 ]Department of Medicine, Division of Clinical Epidemiology, Karolinska Institute, Stockholm, Sweden
                [7 ]Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
                [8 ]Cancer Registry of Norway, Oslo, Norway
                [9 ]Cancer Society of Finland, Finnish Cancer Registry, Helsinki, Finland.
                [10 ]Department of Pediatrics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
                [11 ]Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
                [12 ]Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway
                [13 ]Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
                Author notes
                Correspondence to: D S Daltveit dagrun.daltveit@ 123456uib.no (or @DagrunDaltveit on Twitter)
                Author information
                https://orcid.org/0000-0002-0903-1140
                Article
                daid059263
                10.1136/bmj.m4060
                7708828
                33268348
                52f5570d-87d5-4a81-82db-769f382ae3d6
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 04 October 2020
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                Research

                Medicine
                Medicine

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