Critical points for interpreting patients’ survival rate using cancer registries: A literature review

Journal of Epidemiology

Volumn 28, Issue 2, 2018, Pages 61-66

  Okuyama, Ayako ^a   Shibata, Akiko ^a   Nishimoto, Hiroshi ^a  

^a NATIONAL CANCER CENTER   (Japan)

Author keywords

Neoplasms; Registries; Survival analysis

Indexed keywords

HUMAN; MORTALITY; NEOPLASM; REGISTER; STATISTICAL ANALYSIS; SURVIVAL RATE;

DATA INTERPRETATION, STATISTICAL; HUMANS; NEOPLASMS; REGISTRIES; SURVIVAL RATE;

EID: 85047921284     PISSN: 09175040     EISSN: 13499092     Source Type: Journal    
DOI: 10.2188/jea.JE20160180     Document Type: Review

References (59)

1. Mariotto AB, Noone AM, Howlader N, et al. Cancer survival: an overview of measures, uses, and interpretation. J Natl Cancer Inst Monogr. 2014; 2014: 145-186.
2. Berrino F, De Angelis R, Sant M, et al; EUROCARE Working group. Survival for eight major cancers and all cancers combined for European adults diagnosed in 1995-99: results of the EUROCARE-4 study. Lancet Oncol. 2007; 8: 773-783.
3. Beral V, Peto R. UK cancer survival statistics. BMJ. 2010; 341: c4112.
4. Woods LM, Coleman MP, Lawrence G, et al. Evidence against the proposition that “UK cancer survival statistics are misleading”: simulation study with National Cancer Registry data. BMJ. 2011; 342: d3399.
5. Dixon-Woods M, Cavers D, Agarwal S, et al. Conducting a critical interpretive synthesis of the literature on access to healthcare by vulnerable groups. BMC Med Res Methodol. 2006; 6: 35.
6. Robinson D, Sankila R, Hakulinen T, Møller H. Interpreting international comparisons of cancer survival: the effects of incomplete registration and the presence of death certificate only cases on survival estimates. Eur J Cancer. 2007; 43: 909-913.
7. Holleczek B, Brenner H. Reduction of population-based cancer survival estimates by trace back of death certificate notifications: an empirical illustration. Eur J Cancer. 2012; 48: 797-804.
8. Lake J, Mak V, Møller H, Davies EA. Variation, precision and validity of 1-year survival estimates for lung, breast, colon and prostate cancer in South East England primary care trusts. Public Health. 2012; 126: 57-63.
9. Silcocks P, Thomson CS. Correcting population-based survival for DCOs—why a simple method works and when to avoid it. Eur J Cancer. 2009; 45: 3298-3302.
10. Brenner H, Holleczek B. Deriving valid population-based cancer survival estimates in the presence of nonnegligible proportions of cancers notified by death certificates only. Cancer Epidemiol Biomarkers Prev. 2011; 20: 2480-2486.
11. Innos K, Baburin A, Aareleid T. Cancer patient survival in Estonia 1995-2009: time trends and data quality. Cancer Epidemiol. 2014; 38: 253-258.
12. Brenner H, Hakulinen T. Population-based monitoring of cancer patient survival in situations with imperfect completeness of cancer registration. Br J Cancer. 2005; 92: 576-579.
13. Møller H, Richards S, Hanchett N, et al. Completeness of case ascertainment and survival time error in English cancer registries: impact on 1-year survival estimates. Br J Cancer. 2011; 105: 170-176.
14. Sriamporn S, Swaminathan R, Parkin DM, et al. Loss-adjusted survival of cervix cancer in Khon Kaen, Northeast Thailand. Br J Cancer. 2004; 91: 106-110.
15. Swaminathan R, Rama R, Shanta V. Lack of active follow-up of cancer patients in Chennai, India: implications for population-based survival estimates. Bull World Healthorgan. 2008; 86: 509-515.
16. Brenner H, Hakulinen T. Implications of incomplete registration of deaths on long-term survival estimates from population-based cancer registries. Int J Cancer. 2009; 125: 432-437.
17. Johnson CJ, Weir HK, Yin D, Niu X. The impact of patient followup on population-based survival rates. J Registry Manag. 2010; 37: 86-103.
18. Ganesh B, Swaminathan R, Mathew A, et al. Loss-adjusted hospital and population-based survival of cancer patients. IARC Sci Publ. 2011; 15-21.
19. Rutherford MJ, Møller H, Lambert PC. A comprehensive assessment of the impact of errors in the cancer registration process on 1-and 5-year relative survival estimates. Br J Cancer. 2013; 108: 691-698.
20. Weir HK, Johnson CJ, Mariotto AB, et al. Evaluation of North American Association of Central Cancer Registries’ (NAACCR) data for use in population-based cancer survival studies. J Natl Cancer Inst Monogr. 2014; 2014: 198-209.
21. Pinheiro PS, Morris CR, Liu L, et al. The impact of follow-up type and missed deaths on population-based cancer survival studies for Hispanics and Asians. J Natl Cancer Inst Monogr. 2014; 2014: 210-217.
22. Downing A, West RM, Gilthorpe MS, et al. Using routinely collected health data to investigate the association between ethnicity and breast cancer incidence and survival: what is the impact of missing data and multiple ethnicities? Ethn Health. 2011; 16: 201-212.
23. Woods LM, Rachet B, Ellis L, Coleman MP. Full dates (day, month, year) should be used in population-based cancer survival studies. Int J Cancer. 2012; 131: E1120-E1124.
24. Estève J, Benhamou E, Croasdale M, Raymond L. Relative survival and the estimation of net survival: elements for further discussion. Stat Med. 1990; 9: 529-538.
25. Perme MP, Stare J, Estève J. On estimation in relative survival. Biometrics. 2012; 68: 113-120.
26. Danieli C, Remontet L, Bossard N, et al. Estimating net survival: the importance of allowing for informative censoring. Stat Med. 2012; 31: 775-786.
27. Seppä K, Hakulinen T, Pokhrel A. Choosing the net survival method for cancer survival estimation. Eur J Cancer. 2015; 51: 1123-1129.
28. Roche L, Danieli C, Belot A, et al. Cancer net survival on registry data: use of the new unbiased Pohar-Perme estimator and magnitude of the bias with the classical methods. Int J Cancer. 2013; 132: 2359-2369.
29. Talbäck M, Dickman PW. Estimating expected survival probabilities for relative survival analysis—exploring the impact of including cancer patient mortality in the calculations. Eur J Cancer. 2011; 47: 2626-2632.
30. Hinchliffe SR, Dickman PW, Lambert PC. Adjusting for the proportion of cancer deaths in the general population when using relative survival: a sensitivity analysis. Cancer Epidemiol. 2012; 36: 148-152.
31. Blakely T, Soeberg M, Carter K, et al. Bias in relative survival methods when using incorrect life-tables: lung and bladder cancer by smoking status and ethnicity in New Zealand. Int J Cancer. 2012; 131: E974-E982.
32. Hinchliffe SR, Rutherford MJ, Crowther MJ, et al. Should relative survival be used with lung cancer data? Br J Cancer. 2012; 106: 1854-1859.
33. Ellis L, Coleman MP, Rachet B. The impact of life tables adjusted for smoking on the socio-economic difference in net survival for laryngeal and lung cancer. Br J Cancer. 2014; 111: 195-202.
34. Stroup AM, Cho H, Scoppa SM, et al. The impact of state-specific life tables on relative survival. J Natl Cancer Inst Monogr. 2014; 2014: 218-227.
35. Hakulinen T, Seppä K, Lambert PC. Choosing the relative survival method for cancer survival estimation. Eur J Cancer. 2011; 47: 2202-2210.
36. Howlader N, Ries LA, Mariotto AB, et al. Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010; 102: 1584-1598.
37. Hu CY, Xing Y, Cormier JN, Chang GJ. Assessing the utility of cancer-registry-processed cause of death in calculating cancerspecific survival. Cancer. 2013; 119: 1900-1907.
38. Skyrud KD, Bray F, Møller B. A comparison of relative and causespecific survival by cancer site, age and time since diagnosis. Int J Cancer. 2014; 135: 196-203.
39. Utada M, Ohno Y, Shimizu S, et al. Comparison between overall, cause-specific, and relative survival rates based on data from a population-based cancer registry. Asian Pac J Cancer Prev. 2012; 13: 5681-5685.
40. Charvat H, Bossard N, Daubisse L, et al. Probabilities of dying from cancer and other causes in French cancer patients based on an unbiased estimator of net survival: a study of five common cancers. Cancer Epidemiol. 2013; 37: 857-863.
41. Dickman PW, Auvinen A, Voutilainen ET, Hakulinen T. Measuring social class differences in cancer patient survival: is it necessary to control for social class differences in general population mortality? A Finnish population-based study. J Epidemiol Community Health. 1998; 52: 727-734.
42. Yin D, Morris CR, Bates JH, German RR. Effect of misclassified underlying cause of death on survival estimates of colon and rectal cancer. J Natl Cancer Inst. 2011; 103: 1130-1133.
43. Schaffar R, Rapiti E, Rachet B, Woods L. Accuracy of cause of death data routinely recorded in a population-based cancer registry: impact on cause-specific survival and validation using the Geneva Cancer Registry. BMC Cancer. 2013; 13: 609.
44. Jansen L, Hakulinen T, Brenner H. Study populations for period analyses of cancer survival. Br J Cancer. 2013; 108: 699-707.
45. Brenner H, Hakulinen T. On crude and age-adjusted relative survival rates. J Clin Epidemiol. 2003; 56: 1185-1191.
46. Brenner H, Hakulinen T. Reduction in selective under-ascertainment bias in population-based estimates of cancer patient survival by age adjustment. Eur J Cancer. 2005; 41: 1788-1793.
47. Jansen L, Hakulinen T, Brenner H. Standard errors of nonstandardised and age-standardised relative survival of cancer patients. Br J Cancer. 2012; 106: 569-574.
48. Corazziari I, Quinn M, Capocaccia R. Standard cancer patient population for age standardising survival ratios. Eur J Cancer. 2004; 40: 2307-2316.
49. Pokhrel A, Hakulinen T. Age-standardisation of relative survival ratios of cancer patients in a comparison between countries, genders and time periods. Eur J Cancer. 2009; 45: 642-647.
50. Brenner H, Arndt V, Gefeller O, Hakulinen T. An alternative approach to age adjustment of cancer survival rates. Eur J Cancer. 2004; 40: 2317-2322.
51. Baili P, Micheli A, De Angelis R, et al; CONCORD Working Group. Life tables for world-wide comparison of relative survival for cancer (CONCORD study). Tumori. 2008; 94: 658-668.
52. Rosso S, De Angelis R, Ciccolallo L, et al; EUROCARE Working Group. Multiple tumours in survival estimates. Eur J Cancer. 2009; 45: 1080-1094.
53. Ellison LF. Measuring the effect of including multiple cancers in survival analyses using data from the Canadian Cancer Registry. Cancer Epidemiol. 2010; 34: 550-555.
54. Brenner H, Hakulinen T. Patients with previous cancer should not be excluded in international comparative cancer survival studies. Int J Cancer. 2007; 121: 2274-2278.
55. Sarfati D, Blakely T, Pearce N. Measuring cancer survival in populations: relative survival vs cancer-specific survival. Int J Epidemiol. 2010; 39: 598-610.
56. Weir HK, Johnson CJ, Thompson TD. The effect of multiple primary rules on population-based cancer survival. Cancer Causes Control. 2013; 24: 1231-1242.
57. Dickman PW, Lambert PC. Session 18: Estimating net survival-past and present. Cancer survival: principles, methods and applications. In. 2014.
58. Welch HG, Schwartz LM, Woloshin S. Are increasing 5-year survival rates evidence of success against cancer? JAMA. 2000; 283: 2975-2978.
59. Maruvka YE, Tang M, Michor F. On the validity of using increases in 5-year survival rates to measure success in the fight against cancer. PLoS One. 2014; 9: e83100.