Abstract
Purpose
To test the feasibility of using hospital discharge records (HDR) to monitor frequency indicators of hematologic malignancies (HM) in Abruzzo, an Italian region without a cancer registry.
Methods
Hospital discharge records contain a primary diagnosis field for principal disease and 5 secondary diagnosis fields for other diseases related or not to the principal diagnosis. In order to build patient indicators of HM—non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL), multiple myeloma (MM), and leukemia (acute lymphoblastic leukemia [ALL], chronic lymphoid leukemia [CLL], acute myeloid leukemia [AML], and chronic myeloid leukemia [CML])—residents with first ICD-9-CM code 200-208 in any HDR field, or only in primary field, were identified.
Results
Among 3,955 patients with first diagnosis of HM registered in primary or secondary fields of HDR in the 2009-2013 period, and never recognized in 2005-2008 (791/year) (60.5/100,000), patients with first HM only in primary field were 2,304 (461/year) (35.2/100,000): 42% were NHL, 34% leukemia, 16% MM, 8% HL. Patient percentage of 461/791/year (58%) (64% among ordinary HDR and 49% in day-hospital HDR) was 35% for CLL (28/81), 47% for MM (74/152), 50% for CML (16/32), 57% for HL (36/63), 62% for NHL (194/314), and 82% for ALL (18/22) and AML (64/78).
Conclusions
Applying the cancer registries national rate, expected new diagnoses of HM in Abruzzo are about 620/year (46.4/100,000), compared to HDR estimates of 461 and 791/year (primary/all diagnoses fields: 58%). Since this percentage varies between 35% and 82%, our findings on the 2 methods seem useful for a validation process in the starting Cancer Registry.
Introduction
In Italy, cancer registration is not organized at the national level. Therefore, even though population coverage of registries certified by the Italian Association of Cancer Registries (AIRTUM) is 51%, many local areas are still in need of basic epidemiologic information to support health planning (1). As far as the onco-hematology sector is concerned, AIRTUM data show that hematologic malignancies (HM) account for almost 8% of incidence of all cancers, with a ratio between large areas with the highest and lowest incidence of less than 2 for leukemia, about 2 for non-Hodgkin lymphoma and multiple myeloma, and about 3 for Hodgkin lymphoma (1-2-3-4). Notwithstanding the general relevance of those data, estimates of HM have not been produced at regional level, such as was the case for 7 solid tumors (5, 6). For those reasons, in order to support a more effective delivery of health services and better management of patients with HM in Abruzzo, an Italian region without a cancer registry, hospital discharge records (HDR) were used to estimate and monitor basic frequency indicators of HM.
Methods
Hospital discharge records for 2005-2013, linked using the deterministic technique in respect to the existing rules on privacy rights by the Department for Health Policy of the Abruzzo Regional Authority, were linked with the Health Service resident's registry (updated to September 26, 2014) and provided with anonymous data in October 2014. The matching of HDR with the residents’ registry showed a correct linkage of 95.3%.
Population data were obtained from the National Institute of Statistics (ISTAT) (7).
The HDR contain information on diagnoses and in-hospital death. Diagnoses are coded according to the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) (8). Specifically, in the diagnosis-related groups system, diseases associated with the highest resource consumption are registered in the HDR field “primary diagnosis,” whereas other diseases related or not to the principal diagnosis—such as complications, comorbidities, or procedures for the main condition—are registered in 5 fields called “secondary diagnoses” (primary diagnosis and secondary diagnosis do not mean primary disease and relapsed disease).
For the present analysis, all the available HDR were used, whereas the linked Health Service residents’ registry was used for calculating out-of-hospital deaths.
The HDR with a diagnosis of HM in any field (ICD-9-CM codes 200.00-208.91 [malignant neoplasms of lymphatic and hematopoietic tissue]) were selected from HDR with a diagnosis of cancer in any field (codes 140.00-208.91). From HDR with HM were then selected HM subtypes: non-Hodgkin lymphomas (NHL) (ICD-9-CM codes 200.00-200.88; 202.00-202.98), Hodgkin lymphoma (HL) (201.00-201.98), multiple myeloma and other immunoproliferative neoplasms (MM) (203.00-203.81), total leukemia (204.00-208.91), acute lymphoblastic leukemia (ALL) (204.0), chronic lymphoid leukemia (CLL) (204.1), acute myeloid leukemia (AML) (205.0), and chronic myeloid leukemia (CML) (205.1).
Resident patients with a first diagnosis of any HM registered in the primary or secondary field in 2009-2013—within or out of region, hospitalization or in day-hospital—and therefore with no other hospitalization with HM observed in 2005-2008 were identified. Codes V10.6 and V10.7 were also used to exclude 2005-2008 cases (personal history of leukemia or of lymphatic and other HM [an example of HDR with HM in secondary field is chemotherapy reported in primary diagnosis with first lymphoma registered in secondary field of day-hospital]). Among those residents, patients with a first diagnosis of HM only in the primary field were selected. Of those, patients with no other diagnosis of any cancer recorded throughout the 2005-2013 period were identified.
Absolute numbers and crude rates/100,000 of HM patients were calculated. The average annual percent change (AAPC) of rates was estimated.
The following software was used for statistical analyses: R-Project v.2.15.1 (2012-06-22, The R Foundation for Statistical Computing, Vienna, Austria), Joinpoint Regression Program version 4.1.1, August 2014 (Statistical Research and Applications Branch, National Cancer Institute, Bethesda, MD, USA), and EpiInfo 7.1.4.0 (Centers for Disease Control and Prevention, Atlanta, GA, USA).
Results
In the 2009-2013 period, 16,388 HDR with a diagnosis of HM (3,278/year) and 8,613 patients with one or more hospitalizations with HM (1,723/year) were identified (Tab. I). Among patients with a first diagnosis of any HM in primary or secondary HDR field (3,955; 791/year), 2,304 patients had a first diagnosis of HM only in the primary field (461/year) (58% of all 3,955 patients with first diagnosis). Of those, 2,056 patients had HM and no other diagnosis of cancer throughout the 2005-2013 period (Tab. I).
Distribution of hospital discharge records (HDR) with hematologic malignancies (HM), and of HDR-based patient indicators of HM, for 2009-2013 in Abruzzo
dpx = primary diagnosis field of HDR; sd = secondary diagnoses field of HDR.
Values are absolute number of cases.
A total of 2,460 (62%) ordinary patients had first diagnosis of HM in the primary or secondary field and 1,495 in day-hospital (38%; leukemia: 28%; MM: 40%; NHL: 45%; HL: 49%). Patients with a first diagnosis of HM only in the primary field were 49% in day-hospital patients and 64% in ordinary patients (all patients: 58%) (for example, many day-hospital HDR reported chemotherapy as first diagnosis [V58.1] and a first HM as a secondary diagnosis).
Patients with a first diagnosis of specific HM types in primary or secondary diagnosis, with no other previous HM in 2005-2013, are shown in Table IIA (specific cases sum to 3,969 because of 14 HDR with 2 diagnoses of HM); out of 791 patients/year, cases/year of NHL, leukemia, MM, and HL were 314, 265, 152, and 63 (40%, 33%, 19%, and 8%), respectively.
Absolute numbers of patients with first diagnosis of hematologic malignancies (HM) in primary or secondary diagnosis, and with no other previous HM, by subtype of HM for 2009-2013 in Abruzzo
ALL = acute lymphoblastic leukemia; AML = acute myeloid leukemia; CLL = chronic lymphoid leukemia; CML = chronic myeloid leukemia.
Of 461 patients/year with a first diagnosis of HM only in primary diagnosis, with no other previous HM in 2005-2013, cases/year of NHL, leukemia, MM, and HL were 194, 155, 74, and 36 (42%, 34%, 16%, and 8%), respectively.
In 2009-2013, patients with first diagnosis of leukemia in the primary or secondary field, with no other previous HM, were as follows: 108 for ALL (22/year), 405 for CLL (81/year), 391 for AML (78/year), and 158 for CML (32/year), whereas patients with first diagnosis of leukemia only in the primary field, with no other previous HM, were as follows: 88 for ALL (18/year), 141 for CLL (28/year), 321 for AML (64/year), and 79 for CML (16/year) (81% of total leukemia) (Tab. II, A and B).
Absolute numbers of patients with first diagnosis of hematologic malignancies (HM) only in primary diagnosis, and with no other previous HM, by subtype of HM for 2009-2013 in Abruzzo
ALL = acute lymphoblastic leukemia; AML = acute myeloid leukemia; CLL = chronic lymphoid leukemia; CML = chronic myeloid leukemia.
Patients with first diagnosis of HM in primary diagnosis out of all first patients, with no other previous HM (461/791 [58%]), were 47% for MM, 57% for HL, 59% for leukemia, and 62% for NHL, whereas for specific leukemia were, respectively, 35% for CLL, 50% for CML, 82% for ALL, and 82% for AML (Tab. II).
Patients with a first diagnosis of specific HM in primary or secondary diagnosis, without or with other previous HM, are distributed by year in Table IIIA (cases sum to 4,466). Patients with a first diagnosis of specific HM only in primary diagnosis, without or with other previous HM, are distributed by year in Table IIIB (cases sum to 2,497).
Patients with first diagnosis of hematologic malignancies (HM) in primary or secondary diagnosis, without or with other previous HM, by subtypes of HM for the 2009-2013 period in Abruzzo
ALL = acute lymphoblastic leukemia; AML = acute myeloid leukemia; CLL = chronic lymphoid leukemia; CML = chronic myeloid leukemia; HL = Hodgkin lymphoma; MM = multiple myeloma and other immunoproliferative neoplasms; NHL = non-Hodgkin lymphoma.
Number of cases and average crude rates per 100,000, overall and by sex.
Patients with first diagnosis of hematologic malignancies (HM) only in primary diagnosis, without or with other previous HM, by subtypes of HM for the 2009-2013 period in Abruzzo
ALL = acute lymphoblastic leukemia; AML = acute myeloid leukemia; CLL = chronic lymphoid leukemia; CML = chronic myeloid leukemia; HL = Hodgkin lymphoma; MM = multiple myeloma and other immunoproliferative neoplasms; NHL = non-Hodgkin lymphoma.
Number of cases and average crude rates per 100,000, overall and by sex.
Crude rates of patients with first diagnosis of HM in primary or secondary diagnosis, and of patients with first diagnosis of HM only in primary diagnosis, are reported in Table III, A and B (Abruzzo inhabitants in 2009-2013, average/year: 1,308,001). The AAPC of rates were statistically significant in patients with any HM in primary diagnosis (-3.5%; p<0.05), in patients with HL in primary diagnosis (-12.8%; p<0.05), and in patients with AML in primary diagnosis (+4.8%; p<0.05), and, among female participants only, in patients with ALL and CML in primary or secondary diagnosis (+11.1, +14.1%; p<0.05).
A reference analysis of all cancers was also conducted for the 2009-2013 period (codes 140.0-195.8, 200-208, except 173): patients with first malignant cancer in primary or secondary diagnosis were 7,151/year, whereas patients with first diagnosis of cancer only in primary diagnosis were 5,761/year (81% of all cases).
Among 8,613 patients with one or more hospitalizations in the 2009-2013 period with HM, 1,803 total deaths were registered (360/year) (in-hospital deaths in HDR were 72.5%). Of those, 327 deaths/year occurred among patients with HM in primary diagnosis.
Patients with a first diagnosis of HM in primary diagnosis and no other previous cancer numbered 2,056: 844 (41%) NHL, 701 (34%) leukemia, 345 (17%) MM, and 166 (8%) HL. Among them, overall deaths in the 5-year period numbered 812 (39.5%) in all patients, 389 (55.5%) in patients with leukemia, 152 (44.1%) in MM, 245 (29.0%) in NHL, and 26 (15.7%) in HL.
Discussion
Our analysis was planned to provide, in the frame of the Abruzzo Regional Hematological Plan, readily available epidemiologic information to better support delivery of health services, resource allocation, and management of patients with hematologic malignancies. This study aimed to test the feasibility of using HDR to analyze frequency indicators of HM, since cancer registration was neither available nor yet planned in that period. In fact, even though HDR are collected for administrative reasons, due to the rapid availability of updated information on large numbers of patients, they are increasingly being used both in planning-oriented evaluations and in epidemiologic studies on chronic diseases, representing at the same time a data collection tool for capturing cases in cancer registration systems (9-10-11-12-13-14). However, while some studies show that HDR can be used as a supplementary data source to estimate incidence, other experiences indicate that HDR can only be used to monitor hospital admissions. With respect to hematologic malignancies, HDR-based indicators produced in regions with a cancer registry seem to be consistent with estimates from registry data, but published examples of epidemiologic indicators of HM based only on HDR, and/or conducted in uncovered areas, are few (14, 15). For those reasons, considering that the HDR system is not an alternative data source to a cancer registry, we decided to conduct a simple analysis of frequency indicators of HM in Abruzzo. Realizing that study results refer only to patients with HM needing hospitalization, we observed 791 patients/year with first diagnosis of HM using all diagnosis fields, and 461 patients/year with first diagnosis of HM only in the primary diagnosis field, as 58% of all first cases (vs all cancers: 81%). This frequency was 64% for ordinary hospitalizations and 49% for day-hospital, ranging from 35% for CLL and 47%-50% for MM and CML to 82% for ALL and AML. Therefore, as expected, the predictability of HDR for CLL, CML, and MM was much lower compared to lymphomas and acute leukemia (day-hospital vs ordinary HDR). Since those results cannot be compared with cancer registries, only absolute data for each type of HM by year and crude rates with AAPC were reported (all HM standardized rate with national population was 58/100,000 vs crude rate of 60/100,000). Nevertheless, AIRTUM pooled rates of new diagnosis/year can be simply applied to the Abruzzo population, in order to describe the difference between the 2 indicators, with about 620 expected new cases/year (46.4/100,000) (age-adjusted: 650) (1-2-3-4). In the reference analysis, while the observed new cases of all cancers seem to be lower than the expected/year (7,151 in all diagnosis, and 5,761 in primary diagnosis, vs 8,046), the expected cases of HM are in between the 2 observed figures (620 vs 791 in all diagnosis, and 461 in primary diagnosis) (±27%) (except for AML). Crude expected and observed cases/year, respectively, are approximately as follows: NHL (280-300 vs 314, 194), HL (50 vs 63, 36), MM (110 vs 152, 74), leukemia (170-180 vs 265, 155), ALL (20 vs 22, 18), AML (50 vs 78, 64), CLL (60 vs 81, 28), and CML (25 vs 32, 16).
With regard to those important differences between the 2 indicators, in recent ecologic studies conducted in areas with cancer registry and in uncovered regions, an HDR indicator based only on primary diagnosis has been used for all cancer types including leukemia, NHL, HL, and MM, since this is considered more accurate compared to secondary diagnoses (conservative method with higher specificity: fewer false-positives, although with the risk of reducing the capture of cases: more false-negatives), but the frequency of primary diagnosis out of all cases was not made available (11, 12). Since the indicator based on all diagnoses should have higher sensitivity (fewer false-negatives), and therefore can be more effectively used for capturing hospitalized new cases (although with an increased probability of false-positives to be assessed), we decided to estimate both indicators in order to explore different potential uses (in a previous experience, only new cases with HM in primary or secondary diagnosis in the 2004-2008 period were estimated in Abruzzo: 783/year vs 791/year in 2009-2013) (15).
With respect to our observed results, the limitations of the study have to be discussed. Since HDR have administrative purposes, they cannot be used alone for incidence surveillance of cancer. For this reason, we just analyzed basic indicators to monitor the frequency of patients discharged with HM in Abruzzo. Although using a period of 5 years or more to exclude prevalent cases would have been better, we used the 2005-2008 period to permit a standard 5-year estimate of HM, since HDR data quality of previous years was considered lower by the Health Regional Authority, and a previous analysis was already conducted for the 2004-2008 period (15). For this reason, due to the risk of increasing prevalent cases particularly in 2009, absolute numbers for all the 5 years were analyzed: figures were rather stable, and AAPC was statistically significant in only a few trends, such as HL (decreasing) and AML (increasing). In this respect, while some studies used few years, recent studies did not exclude prevalent cases at all (11-12-13). Those different methodologic approaches may be due to diverse uses of HDR indicators. The aim of our study was, in fact, to give a basic description of HM frequency in Abruzzo using available data. Therefore, given that HM represent a group of heterogeneous diseases in terms of prognosis, treatments, and hospitalization in relation to the ICD-9-CM system, an implicit validation method has been applied to each type of HM, and, as expected, the observed results showed that the predictability of HDR for CLL, CML, and MM was much lower compared to lymphomas and acute leukemia. Even though the ICD-9-CM is not accurate enough to provide epidemiologic data, this system has been used since in HDR diagnoses are coded with this classification, and the results have been compared with AIRTUM pooled data classified in the same groups with ICD-10 (NHL, HL, MM, all leukemia, ALL, CLL, AML, CML). In this respect, a validation process to confirm histologic subtypes with the ICD-O-3 has to be planned within the starting cancer registry; as a first step, a linkage for trans-coding ICD-9-CM primary diagnosis codes of HM in ICD-O-3 produced a concordance of 65%. Concerning other diseases, although many cancer registries include Waldenstrom macroglobulinemia (273.3), it was not included in our analysis since new cases/year in all diagnosis and in primary diagnosis were 12 and 5. Finally, since 10% of HDR deaths were not recorded in the residents’ registry, HDR were used for calculating in-hospital deaths, and simple analysis showed that 360 deaths/year were registered among prevalent patients with HM (73% in HDR), 327 of which were in patients with HM as a primary diagnosis; in the same period, deaths/year from ISTAT mortality rates were 310-320 (ICD-9 200-208).
With regards to those limitations, several studies have examined the accuracy of HDR in epidemiologic studies on cancers and other chronic diseases (9-10-11-12-13-14-15-16-17-18). Even though cautioning because of problems with quality, such as failure to identify prevalent cases or inaccuracies in coding diagnoses, those studies conclude that HDR are a valuable data source for integrating cancer estimation and registration, but few Italian experiences on HM are available. For those reasons, considering that HDR is one of the sources already used by cancer registries, our experience could represent an opportunity for its specific implications in heterogeneous diseases such as HM.
Since the same databases have been made available to the starting Cancer Registry of Abruzzo, the 330 cases/year with first HM in secondary diagnoses, and then the 461/year primary diagnoses, can be validated with other data sources (e.g., primary diagnoses of chemotherapy, radiotherapy, sepsis, fever, or complications of bone marrow transplantation in cases with first HM in secondary fields). Specifically, 2012-2013 can be used, with 7-8 years to exclude prevalent cases, and, possibly, ambulatory records can be included. Moreover, our exploratory analysis of transcoded ICD-9-CM HDR with ICD-O-3 can be fully implemented.
Overall, notwithstanding the well-known limitations of HDR, our study provides basic indicators of frequency to monitor HM in Abruzzo. Moreover, since the Regional Cancer Registry has been regulated recently, our analysis could give useful information on HDR for registry implementation, as far as HM are concerned.
Footnotes
Financial support: The presented work was funded by the fellowship related to the Project “Epidemiologia assistenziale in pazienti con patologie onco-ematologiche e con diversi gradi di complessità clinico-assistenziale” deliberated by ASL of Pescara (Delibere n. 1111, 14.11.2013; n. 805, 31.07.2013) with a budget of the Abruzzo “Regional Haematological Plan” deliberated by ASL of Pescara (Delibera n. 509, 16.05.2013), and was partially funded by the “A.I.L. Associazione Italiana contro le Leucemie-linfomi e mieloma Onlus - Sezione Interprovinciale di Pescara-Teramo”, and by the “Fondazione P.C.F.F. Pescara Cell Factory Foundation Onlus - Stem Cells and Regenerative Medicine Research Foundation”.
Conflict of interest: None of the authors has conflict of interest with this submission.