A POPULATION-BASED STUDY ON MYELODYSPLASTIC SYNDROMES IN THE LAZIO REGION (ITALY), MEDICAL MISCODING AND 11-YEAR MORTALITY FOLLOW-UP: THE GRUPPO ROMANO-LAZIALE MIELODISPLASIE EXPERIENCE OF RETROSPECTIVE MULTICENTRIC REGISTRY
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Keywords
myelodysplastic syndromes, epidemiology, medical miscoding
Abstract
Results on myelodysplastic syndromes (MDS) from population-based studies are rare and these data are infrequently collected by cancer registries because diagnostic difficulties and under-reported data.
Our is the first regional Lazio study about medical coding, diagnosis, classification and mortality of MDS patients. This study is aimed at evaluating MDS medical miscoding and conducting a mortality follow-up in a cohort of 644 MDS patients enrolled in the Gruppo Romano-Laziale Mielodisplasie (GROM-L) registry from 2002 to 2010.
We linked the MDS cohort with 2 regional health information systems: the Hospital Information System (HIS) and the regional Mortality Information System (MIS).
About the first objective 92% of the patients had at most 12 hospitalization, but 28.5% of them had no hospitalization with the 238.7 ICD-9-CM. About the second objective we observed 45.5% of death during the follow-up, Myelodysplastic Syndrome was the second cause of death, other frequent causes of death were myeloid leukemia and aplastic anemia.
This study highlights for the first time in Lazio that a disease like MDS, involving many resources for care assistance, tends to be under-documented in the HIS archive. This may be due to the evolution of the disease over the time, the inappropriate use of existing ICD-9-CM and the limitations of current ICD-9-CM classification. Moreover, the most frequent causes of death other than MDS might suggest a miscoding of MDS in the death causes too.
In conclusion our registry could be a useful investigational tool to make a continued surveillance on medical miscoding and collect epidemiological data.
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References
2. Dinmohamed AG, Visser O, van Norden Y, Huijgens PC, Sonneveld P, van de Loosdrecht AA, et al. Trends in incidence, initial treatment and survival of myelodysplastic syndromes: a population-based study of 5144 patients diagnosed in the Netherlands from 2001 to 2010. Eur J Cancer. 2014 Mar;50(5):1004-12.
3. Neukirchen J, Schoonen WM, Strupp C, Gattermann N, Aul C, Haas R, et al. Incidence and prevalence of myelodysplastic syndromes: data from the Dusseldorf MDS-registry. Leuk Res. 2011 Dec;35(12):1591-6.
4. Nomdedeu M, Pereira A, Ramos F, Valcarcel D, Costa D, Arnan M, et al. Excess mortality in the myelodysplastic syndromes. Am J Hematol. 2016 Nov 14.
5. Zeidan AM, Wang R, Davidoff AJ, Ma S, Zhao Y, Gore SD, et al. Disease-related costs of care and survival among Medicare-enrolled patients with myelodysplastic syndromes. Cancer. 2016 May 15;122(10):1598-607.
6. Neukirchen J, Nachtkamp K, Schemenau J, Aul C, Giagounidis A, Strupp C, et al. Change of prognosis of patients with myelodysplastic syndromes during the last 30 years. Leuk Res. 2015 Jul;39(7):679-83.
7. Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G, et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997 Mar 15;89(6):2079-88.
8. Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Sole F, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012 Sep 20;120(12):2454-65.
9. Malcovati L, Germing U, Kuendgen A, Della Porta MG, Pascutto C, Invernizzi R, et al. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes. J Clin Oncol. 2007 Aug 10;25(23):3503-10.
10. Gangat N, Patnaik MM, Tefferi A. Myelodysplastic syndromes: Contemporary review and how we treat. Am J Hematol. 2016 Jan;91(1):76-89.
11. Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016 May 19;127(20):2391-405.
12. World Health Organization. ICD website. (cited, available: http://www.cdc.gov/nchs/icd/icd9.htm).
13. Epiclin website (cited, available: https://www.epiclin.it/mds_registro).
14. Cascini S, Agabiti N, Incalzi RA, Pinnarelli L, Mayer F, Arca M, et al. Pneumonia burden in elderly patients: a classification algorithm using administrative data. BMC Infect Dis. 2013;13:559.
15. Cesaroni G, Agabiti N, Forastiere F, Perucci CA. Socioeconomic differences in stroke incidence and prognosis under a universal healthcare system. Stroke. 2009 Aug;40(8):2812-9.
16. Di Domenicantonio R, Cappai G, Arca M, Agabiti N, Kohn A, Vernia P, et al. Occurrence of inflammatory bowel disease in central Italy: a study based on health information systems. Dig Liver Dis. 2014 Sep;46(9):777-82.
17. Roberto G, Leal I, Sattar N, Loomis AK, Avillach P, Egger P, et al. Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project. PLoS One. 2016;11(8):e0160648.
18. Moretz C, Zhou Y, Dhamane AD, Burslem K, Saverno K, Jain G, et al. Development and Validation of a Predictive Model to Identify Individuals Likely to Have Undiagnosed Chronic Obstructive Pulmonary Disease Using an Administrative Claims Database. J Manag Care Spec Pharm. 2015 Dec;21(12):1149-59.
19. Dinmohamed AG, van Norden Y, Visser O, Posthuma EF, Huijgens PC, Sonneveld P, et al. The use of medical claims to assess incidence, diagnostic procedures and initial treatment of myelodysplastic syndromes and chronic myelomonocytic leukemia in the Netherlands. Leuk Res. 2015 Feb;39(2):177-82.
20. Orazi A. Histopathology in the diagnosis and classification of acute myeloid leukemia, myelodysplastic syndromes, and myelodysplastic/myeloproliferative diseases. Pathobiology. 2007;74(2):97-114.
21. Rollison DE, Howlader N, Smith MT, Strom SS, Merritt WD, Ries LA, et al. Epidemiology of myelodysplastic syndromes and chronic myeloproliferative disorders in the United States, 2001-2004, using data from the NAACCR and SEER programs. Blood. 2008 Jul 1;112(1):45-52.
22. Bennett JM. A comparative review of classification systems in myelodysplastic syndromes (MDS). Semin Oncol. 2005 Aug;32(4 Suppl 5):S3-10.
23. Komrokji RS, Matacia-Murphy GM, Al Ali NH, Beg MS, Safa MM, Rollison DE, et al. Outcome of patients with myelodysplastic syndromes in the Veterans Administration population. Leuk Res. 2010 Jan;34(1):59-62.
24. Ma X. Epidemiology of myelodysplastic syndromes. Am J Med. 2012 Jul;125(7 Suppl):S2-5.
25. Polednak AP, Phillips C. Coding of specific subgroups of myelodysplastic syndromes in a population-based cancer registry: prospects for improvement. J Registry Manag. 2012 Fall;39(3):107-14.
26. Ma X, Does M, Raza A, Mayne ST. Myelodysplastic syndromes: incidence and survival in the United States. Cancer. 2007 Apr 15;109(8):1536-42.
27. Voso MT, Fenu S, Latagliata R, Buccisano F, Piciocchi A, Aloe-Spiriti MA, et al. Revised International Prognostic Scoring System (IPSS) predicts survival and leukemic evolution of myelodysplastic syndromes significantly better than IPSS and WHO Prognostic Scoring System: validation by the Gruppo Romano Mielodisplasie Italian Regional Database. J Clin Oncol. 2013 Jul 20;31(21):2671-7.
28. Polednak AP, Phillips C. Leukemia as a cause of death among patients with myelodysplastic syndromes (MDS) in a population- based cancer registry: improving estimates of MDS-related mortality in the population. J Registry Manag. 2012 Fall;39(3):115-20.