Diagnostic codes of cancer in Skåne healthcare register : a validation study using individual-level data in southern Sweden
Shen, Qing ; Schelin, Maria E.C. LU ; Fang, Fang and Jöud, Anna LU
(2021)
In BMC Cancer
21(1).
- Abstract
Background: The Swedish healthcare is decentralised to 21 regions. Detailed information on all delivered care in the southernmost region, Skåne, is prospectively collected in the Skåne Healthcare Register (SHR). The data is updated daily and hence a good source for epidemiological studies. However, the diagnostic codes used to identify cancer patients in SHR have not yet been validated. Methods: We conducted a validation study including 1,473,204 residents in Skåne region during 2005–2014, with at least one physical consultation in SHR. Newly diagnosed cancer from the Swedish Cancer Register was considered the ‘gold standard’ reference. We estimated the positive predictive value (PPV), sensitivity, and area under the curve (AUC) of a... (More)
Background: The Swedish healthcare is decentralised to 21 regions. Detailed information on all delivered care in the southernmost region, Skåne, is prospectively collected in the Skåne Healthcare Register (SHR). The data is updated daily and hence a good source for epidemiological studies. However, the diagnostic codes used to identify cancer patients in SHR have not yet been validated. Methods: We conducted a validation study including 1,473,204 residents in Skåne region during 2005–2014, with at least one physical consultation in SHR. Newly diagnosed cancer from the Swedish Cancer Register was considered the ‘gold standard’ reference. We estimated the positive predictive value (PPV), sensitivity, and area under the curve (AUC) of a cancer diagnosis based on SHR by level of consultation, for any cancer, and for different cancer types. Results: There were 61,693 cancers from the Swedish Cancer Register, and 87,650 cancers from SHR. The PPV of SHR-based diagnosis of any cancer was 63.76% (95% confidence interval (CI): 63.44–64.08%) with a sensitivity of 90.58% (95% CI: 90.35–90.81%). The AUC was 0.94, for any cancer. The measures of PPV, sensitivity and AUC varied across levels of care and were higher in specialized care than in primary care. The highest PPV was observed for specialist inpatient care in SHR (89.17, 95% CI 88.89–89.45%) whereas the highest sensitivity was observed for specialized outpatient care in SHR (86.39, 95%CI 86.12–86.66%). Robust validity was noted among most cancers, except for cancers of soft tissues, central nervous system and eye, and endocrine glands. Conclusions: Our study supports that SHR is a valid and robust healthcare register for cancer diagnosis, with varying validities across levels of care and cancer types. This makes SHR a useful data source for cancer epidemiological studies, especially because the data covers the entire cancer care pathways without time lags for further linkage.
(Less)
- author
- Shen, Qing
; Schelin, Maria E.C.
LU
; Fang, Fang
and Jöud, Anna
LU
- organization
- publishing date
- 2021-12-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Cancer diagnosis, Healthcare, Register-based, Validity
- in
- BMC Cancer
- volume
- 21
- issue
- 1
- article number
- 759
- publisher
- BioMed Central (BMC)
- external identifiers
-
- scopus:85109032377
- pmid:34193086
- ISSN
- 1471-2407
- DOI
- 10.1186/s12885-021-08481-5
- language
- English
- LU publication?
- yes
- id
- 23ddb4ba-5b2e-49e3-a230-821fe50982bd
- date added to LUP
- 2021-08-12 11:13:30
- date last changed
- 2024-06-15 14:14:36
@article{23ddb4ba-5b2e-49e3-a230-821fe50982bd,
abstract = {{<p>Background: The Swedish healthcare is decentralised to 21 regions. Detailed information on all delivered care in the southernmost region, Skåne, is prospectively collected in the Skåne Healthcare Register (SHR). The data is updated daily and hence a good source for epidemiological studies. However, the diagnostic codes used to identify cancer patients in SHR have not yet been validated. Methods: We conducted a validation study including 1,473,204 residents in Skåne region during 2005–2014, with at least one physical consultation in SHR. Newly diagnosed cancer from the Swedish Cancer Register was considered the ‘gold standard’ reference. We estimated the positive predictive value (PPV), sensitivity, and area under the curve (AUC) of a cancer diagnosis based on SHR by level of consultation, for any cancer, and for different cancer types. Results: There were 61,693 cancers from the Swedish Cancer Register, and 87,650 cancers from SHR. The PPV of SHR-based diagnosis of any cancer was 63.76% (95% confidence interval (CI): 63.44–64.08%) with a sensitivity of 90.58% (95% CI: 90.35–90.81%). The AUC was 0.94, for any cancer. The measures of PPV, sensitivity and AUC varied across levels of care and were higher in specialized care than in primary care. The highest PPV was observed for specialist inpatient care in SHR (89.17, 95% CI 88.89–89.45%) whereas the highest sensitivity was observed for specialized outpatient care in SHR (86.39, 95%CI 86.12–86.66%). Robust validity was noted among most cancers, except for cancers of soft tissues, central nervous system and eye, and endocrine glands. Conclusions: Our study supports that SHR is a valid and robust healthcare register for cancer diagnosis, with varying validities across levels of care and cancer types. This makes SHR a useful data source for cancer epidemiological studies, especially because the data covers the entire cancer care pathways without time lags for further linkage.</p>}},
author = {{Shen, Qing and Schelin, Maria E.C. and Fang, Fang and Jöud, Anna}},
issn = {{1471-2407}},
keywords = {{Cancer diagnosis; Healthcare; Register-based; Validity}},
language = {{eng}},
month = {{12}},
number = {{1}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Cancer}},
title = {{Diagnostic codes of cancer in Skåne healthcare register : a validation study using individual-level data in southern Sweden}},
url = {{http://dx.doi.org/10.1186/s12885-021-08481-5}},
doi = {{10.1186/s12885-021-08481-5}},
volume = {{21}},
year = {{2021}},
}