Subscribe to RSS
DOI: 10.1160/ME0299
Errors in Survival Rates Caused by Routinely Used Deterministic Record Linkage Methods
Publication History
Publication Date:
20 January 2018 (online)
Summary
Objective: It was the objective of this study to assess the impact of applying various record linkage methods to one of the most important outcome measures in oncological epidemiology, namely survival rates.
Methods: To assess the life status of patients, incidence data published by the Cancer Registry of Tyrol were analyzed with three routinely used methods of record linkage for incidence and mortality data. Of these methods, two were deterministic and the third a probabilistic method developed by the Cancer Registry of Tyrol. We studied the impact of record linkage methods on a simple measure (mortality rate) and a more complex measure (relative survival rate). The analysis was based on the published incidence data for Tyrol for the years 1992 to 1996. Results of deterministic record linkage methodswere simulated.
Results: The error rates for simple mortality rate and relative survival rate are considerable. For the first deterministic record linkage method, relative differences in mortality rate range from 11.9% to 14.8% (men) and 24.5% to 28.2% (women) and relative differences in relative five-year survival from 11.4% to 16.3% (men) and from 19.3% to 26.4% (women). For the second deterministic record linkage method, relative differences in mortality rate range from 4.8% to 5.9% (men) and from 4.9% to 7.4% (women), while relative differences in relative five-year survival range from 5.1% to 7.0% (men) and from 4.4% to 6.1% (women).
Conclusions: Our study shows that in order to calculate valid mortality and survival rates a probabilistic method of record linkage must be applied.
-
References
- 1 Coleman MP, Gatta G, Verdecchia A, Esteve J, Sant M, Storm H, Allemani C, Ciccolallo L, Santaquilani M, Berrino F. EUROCARE-3 summary: cancer survival in Europe at the end of the 20th century. Ann Oncol. 2003: V128-V149.
- 2 Coebergh JW, Sant M, Berrino F, Verdecchia A. Survival of Adult Cancer Patients in Europe Diagnosed from 1978-1989: The Eurocare II Study. Eur J Cancer. 1998
- 3 Brenner H, Hakulinen T. Very-long-term survival rates of patients with cancer. J Clin Oncol. 2002: 4405-9.
- 4 SEER Program version(2001): SEER*Stat 4.0.9, Data Incidence – SEER 9, Registries Public Use (1973-1998). 2000.
- 5 Parkin DM, Whelan SL, Ferlay J, Teppo L, Thomas B. Cancer Incidence in Five Continents. Volume VIII. Lyon: 2002.
- 6 Brenner H, Schmidtmann I. Determinants of homonym and synonym rates of record linkage in disease registration. Methods Inf Med 1996; 35: 19-24.
- 7 Newman TB, Brown AN. Use of commercial record linkage software and vital statistics to identify patient deaths. J Am Med Inform Assoc. 1997: 233-7.
- 8 Quantin C, Bouzelat H, Allaert FA, Benhamiche AM, Faivre J, Dusserre L. How to ensure data security of an epidemiological follow-up: quality assessment of an anonymous record linkage procedure. Int J Med Inf. 1998: 117-22.
- 9 Gomatam S, Carter R, Ariet M, Mitchell G. An empirical comparison of record linkage procedures. Stat Med. 2002: 1485-96.
- 10 van den Brandt P, Schouten LJ. Development of a Record Linkage Protocol for Use in the Dutch Cancer Registry for Epidemiological Research. IntJEpid. 1990: 553-8.
- 11 Oberaigner W, Stühlinger W. Record Linkage in the Cancer Registry of Tyrol, Austria. Methods Inf Med 2005; 44 (05) 626-30.
- 12 Verykios VS, Moustakides GV, Elfeky MG. A Bayesian decision model for cost optimal record matching. Vldb Journal. 2003: 28-40.
- 13 Dal Maso L, Braga C, Franceschi S. Methodology used for “Software for automated linkage in Italy” (SALI)(1). Journal of Biomedical Informatics. 2001: 387-95.
- 14 Jaro MA. Probabilistic Linkage of Large Public Health Data Files. Stat Med 1995; 14: 491-8.
- 15 Oberaigner W, Mühlböck H, Harrasser L. Tumorregister Tirol – Bericht für die Diagnosejahre 1997/98. Innsbruck: 2003.
- 16 Parkin DM, Whelan SL, Ferlay J, Raymond L, Yuen J. Cancer Incidence in Five Continents. Volume VII. Lyon: IARC; 1997.
- 17 Hakulinen T, Abeywickrama KH. A computer program package for relative survival analysis. Comp Progr in Biomed. 1985: 197-207.
- 18 Voutilainen ET, Dickman PW, Hakulinen T. SURV 3 – Relative Survival Analysis. Program Version 3.00b1. Helsinki: Finish Cancer Registry; 2001.
- 19 Muhlberger V, Greil V, Stuhlinger W, Pachinger O. Mortality analysis 2 years after invasive cardiologic interventions in Innsbruck in the year of 1998 by record linkage of the “Statistik Österreich”. Herz; 2001: 495-500.
- 20 Bopp M, Minder CE. Mortality by education in German speaking Switzerland, 1990-1997: results from the Swiss National Cohort. International Journal of Epidemiology. 2003: 346-54.
- 21 Garcia M, Schiaffino A, Fernandez E, Marti M, Salto E, Perez G, Peris M, Borrell C, Nieto FJ, Borras JM. The Cornella Health Interview Survey Follow-Up (CHIS. FU) study: design, methods, and response rate. Bmc Public Health; 2003: 12.
- 22 Morgan CL, Kerr MP. Epilepsy and mortality: A record linkage study in a UK population. Epilepsia. 2002: 1251-5.
- 23 Grannis SJ, Overhage JM, Hui S, McDonald CJ. Analysis of a Probabilistic Record Linkage Technique without Human Review. Proc AMIA Symp. 2003: 259-63.
- 24 Adams MM, Wilson HG, Casto DL, Berg CJ, McDermott JM, Gaudino JA, McCarthy BJ. Constructing reproductive histories by linking vital records. Am J Epidemiol. 1997: 339-48.
- 25 Alsop JC, Langley JD. Determining first admissions in a hospital discharge file via record linkage. Methods Inf Med 1998; 37: 32-7.
- 26 Liu S. Development of record linkage of hospital discharge data for the study of neonatal readmission. Chronic Dis Can. 1999: 77-81.
- 27 Kendrick SW, Douglas MM, Gardner D, Hucker D. Best-link matching of Scottish health data sets. Methods Inf Med 1998; 37: 64-8.
- 28 Potosky AL, Riley GF, Lubitz JD, Mentnech RM, Kessler LG. Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care. 1993: 732-48.