Literature DB >> 9303369

Data quality in population-based cancer registration: an assessment of the Merseyside and Cheshire Cancer Registry.

D J Seddon1, E M Williams.   

Abstract

Merseyside and Cheshire Cancer Registry (MCCR) data quality was assessed by applying literature-based measures to 27,942 cases diagnosed in 1990 and 1991. Registrations after death (n = 8535) were also audited (n = 917) to estimate death certificate only (DCO) case accuracy and the proportion of registrations notified by death certificate (DC). Ascertainment appeared to be high from the registration/mortality ratio for lung [1.01:1] and to be low from capture-recapture estimates (59.4%), varying significantly with site from oesophagus [92.2% (95% CI 88.5-95.9)] to breast [47.5 (95% CI 41.8-53.2)]. The estimated DC-dependent proportion was 20% (5601 out of 27 942) with successful traceback in 3533 out of 5601 (63.1%) cases. DCO flagging (2497 out of 27,942, 8.9%) overestimated true DCO cases (2068 out of 27,942, 7.4%). The proportion of cases of unknown primary site was low (1.5%), varying significantly with age [0-4.2%, (95% CI 2.5-5.9)] and district [0.8% (95% CI 0.3-1.3) to 2.2% (95% CI 1.8-2.6)]. The median diagnosis to registration interval appeared to be good (10 weeks), varying significantly with site (P < 0.0001), age (P < 0.0001) and district (P < 0.0001). The proportion with a verified diagnosis was 77.3%, varying significantly with site [lung 55.2% (95% CI 53.7-56.7) to cervix 96.9% (95% CI 96.3-97.5)], age [45.2% (95% CI 40.9-49.5) to 97.5% (95% CI 96.4-98.6)] and district [71.8% (95% CI 69.9-73.8) to 82.5% (95% CI 80.7-84.3)]. The DCO percentages varied similarly by site [non-melanoma skin 0.4% (95% CI 0.2-0.6) to lung 22.6% CI (95% 19.9-25.3)], age [0.7(95% CI 0.1-1.4) to 23.0 (95% CI 19.4-26.6)] and district [6.9% (95% CI 5.7-8.1) to 13.9% (95% CI 12.9-15.0)]. MCCR data quality varied with age, site and district - inviting action - and apparently compares favourably with elsewhere, although deficiencies in published data hampered definitive assessment. Putting quality assurance into practice identified shortcomings in the scope, definition and application of existing measures, and absent standards impeded interpretation. Cancer registry quality assurance should henceforward be within an explicit framework of agreed and standardized measures.

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Year:  1997        PMID: 9303369      PMCID: PMC2228008          DOI: 10.1038/bjc.1997.443

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


  6 in total

1.  An application of capture-recapture methods to the estimation of completeness of cancer registration.

Authors:  S C Robles; L D Marrett; E A Clarke; H A Risch
Journal:  J Clin Epidemiol       Date:  1988       Impact factor: 6.437

2.  Cancer registration: integrate or disintegrate?

Authors:  N E Day; T W Davies
Journal:  BMJ       Date:  1996-10-12

3.  National cancer registration: an appraisal.

Authors:  R Balarajan; A Scott
Journal:  Community Med       Date:  1983-02

4.  Estimation of completeness of cancer registration.

Authors:  R T Benn; I Leck; U P Nwene
Journal:  Int J Epidemiol       Date:  1982-12       Impact factor: 7.196

5.  Variations in the level of reporting by hospitals to a regional cancer registry.

Authors:  L S Freedman
Journal:  Br J Cancer       Date:  1978-05       Impact factor: 7.640

6.  Completeness of cancer and death follow-up obtained through the National Health Service Central Register for England and Wales.

Authors:  M M Hawkins; A J Swerdlow
Journal:  Br J Cancer       Date:  1992-08       Impact factor: 7.640

  6 in total
  8 in total

Review 1.  Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

Authors:  Danielle G T Arts; Nicolette F De Keizer; Gert-Jan Scheffer
Journal:  J Am Med Inform Assoc       Date:  2002 Nov-Dec       Impact factor: 4.497

2.  Analysis of data errors in clinical research databases.

Authors:  Saveli I Goldberg; Andrzej Niemierko; Alexander Turchin
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

3.  Concordance on the recording of cancer in the Saskatchewan Cancer Agency Registry, hospital charts and death registrations.

Authors:  N S Rawson; D L Robson
Journal:  Can J Public Health       Date:  2000 Sep-Oct

4.  "Summary Page": a novel tool that reduces omitted data in research databases.

Authors:  Saveli I Goldberg; Andrzej Niemierko; Maria Shubina; Alexander Turchin
Journal:  BMC Med Res Methodol       Date:  2010-10-08       Impact factor: 4.615

5.  Error rates in a clinical data repository: lessons from the transition to electronic data transfer--a descriptive study.

Authors:  Matthew K H Hong; Henry H I Yao; John S Pedersen; Justin S Peters; Anthony J Costello; Declan G Murphy; Christopher M Hovens; Niall M Corcoran
Journal:  BMJ Open       Date:  2013-05-28       Impact factor: 2.692

6.  Breast cancer histological classification: agreement between the Office for National Statistics and the National Health Service Breast Screening Programme.

Authors:  Toral Gathani; Diana Bull; Jane Green; Gillian Reeves; Valerie Beral
Journal:  Breast Cancer Res       Date:  2005-11-09       Impact factor: 6.466

7.  Bayesian estimation of a cancer population by capture-recapture with individual capture heterogeneity and small sample.

Authors:  Laurent Bailly; Jean Pierre Daurès; Brigitte Dunais; Christian Pradier
Journal:  BMC Med Res Methodol       Date:  2015-04-24       Impact factor: 4.615

8.  Socioeconomic variation in colon cancer tumour factors associated with poorer prognosis.

Authors:  G Lyratzopoulos; C R West; E M I Williams
Journal:  Br J Cancer       Date:  2003-09-01       Impact factor: 7.640

  8 in total

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