A population-based analysis of invasive fungal disease in haematology-oncology patients using data linkage of state-wide registries and administrative databases: 2005 - 2016

Invasive fungal disease (IFD) represents a significant challenge in the management of patients with haematological malignancies (HM) undergoing cytotoxic chemotherapy and/or haematopoietic stem cell transplantation (HSCT) [1]. IFD is associated with a high mortality ranging from 29-90% [1, 2] and may affect long-term leukaemia outcomes by delaying or modifying curative chemotherapy or HSCT [3]. Few studies have evaluated the value of data linkage for IFD surveillance [4] and none have focused on the disease burden of these infections at a population-level in Victoria, Australia.

Administrative datasets are an efficient source of epidemiological data [5], yet their utility for IFD surveillance in Australia has not been well studied. The only population-based analysis of IFD in Australia used hospital discharge-coded data from 1995 to 1999 and showed that invasive candidiasis (IC) was more common than invasive aspergillosis (IA) representing 0.36% and 0.03% of all acute hospital discharges, respectively, and were associated with mortality rates between 8–26% for both IC and IA [4]. Importantly, these data predated the introduction of broad-spectrum triazole antifungal drugs that have resulted in a shift in fungal epidemiology to filamentous moulds [6] and it excluded the second most populous state in Australia, namely Victoria, with a population of 6.39 million residents [7]. The availability of state-based datasets has afforded an opportunity to revisit IFD disease burden and trends among haematology patients capturing the era of potent mould-active antifungal therapies and improvements in supportive care in cancer [8].

In this study, we linked existing population-based datasets and state registry data to characterise the epidemiology of IFD among the HM and HSCT populations across Victoria. The Victorian Admitted Episodes Dataset (VAED) is Australia’s largest hospital morbidity database and comprises demographic, administrative and clinical information coded according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) associated with every hospitalisation in Victorian public and private hospitals [9]. The Victorian Cancer Registry (VCR) has recorded all cancer diagnoses from 1982 with the exception of basal and squamous cell carcinomas of the skin in Victorian residents [10], but is only available for haematological malignancies from 1^st January 2008 to the 31^st December 2014. Overall, in-hospital and out-of-hospital mortality was evaluated with linkage to the Victorian Death Index (VDI), thus allowing comparisons of survival in patients with and without IFD. We performed data linkage between the VAED, VCR and VDI to characterise the epidemiology of IFD at a population-level over a decade in order to evaluate trends, risk-factors and to identify patient groups at high-risk for IFD.

This is the first comprehensive study of IFD incidence and survival in Victoria among haematology patients over a period of 11 years and highlights the possibilities of data linkage, but also the shortcomings of administrative data for surveillance of a rare disease. The most striking finding from this study is the low overall incidence of IFD among HM-patients (2.04%) and HSCT-recipients (6.29%). It is likely that IFD is under-reported at a hospital level in coding data [14, 15] and this translates into the data generated by the VAED. Despite this shortcoming, we were able to identify periods of high-risk for a range of HMs, seasonal trends in IFD and an overall decrease in IFD incidence over the 11 years. In addition, access to a high number of clinical covariates allowed for exploration of risk-factors for IFD through multivariate regression analysis that may assist in tailoring preventative therapies like antifungal prophylaxis according to individual risk.

The epidemiological trends in IFD incidence and mortality in the HM population has historically been limited to institutional-specific reports and multicentre studies focusing predominantly on IA, IC and mucormycosis [1, 4, 16]. By contrast, through data linkage of hospital administrative data (VAED) with state-based registries (VCR and VDI), we described epidemiological trends among all HM-patients. Mould diseases predominated in keeping with global trends [6], accounting for 61% of IFD compared to 39% due to invasive candidiasis. Among mould diseases, IA was the predominant species (91%), followed by mucormycosis (8.76%); a finding concordant with recent studies [17, 18]. Mucormycosis most commonly affected allo-HSCT-recipients (1.19%), followed by ALL (0.75%) and AML (0.45%) patients and was associated with the shortest median survival time of 3-months compared to 7-months each for IA and IC. The emergence of mucormycosis as the predominant non-Aspergillus mould is consistent with the largest multicentre surveillance study of IFD epidemiology in HSCT recipients [6] and is likely due to several factors including longer survival post-HSCT [6, 19].

A higher IFD incidence (11%) in ALL compared to AML (9.42%) is intriguing but confirms that the ALL cohort is an emerging subgroup at high-risk of IFD with a variable fungal incidence ranging from 6.5-12% [20, 21]. Prophylaxis with azole antifungals is contra-indicated due to the drug-drug interactions with vinca alkaloids used in ALL treatment regimens [22]; but the lack of an approved standard of care from clinical trial data [21] means that clinical variation in prophylactic strategies for ALL patients is likely [23]. Patients with CLL have the third-highest IFD incidence (1.33%) and are increasingly recognised as being at high-risk of IFD due to a shift from chemo-immunotherapies to agents targeting specified B-lymphocyte pathways [24]. Indeed, IFD incidence in non-Hodgkin lymphoma (NHL) (1.26%) was the fourth highest of all HM (Table 2) which may reflect the effects of multi-agent chemotherapy in combination with immunotherapy used to treat NHL [25].

Attempts at clinical risk-stratification for IFD have been crude and restricted to broadly identifying low-, intermediate- and high-risk groups [20] in a large part because large datasets for a rare disease like IFD do not exist [26]. We confirmed risk-factors that are associated with IFD including viral infections [27], admission to a rural hospital that may reflect rural place of residence [20] and Clostridium difficile infection (p<0.05) which has not been previously described as a risk-factor for IFD but is prevalent in immunocompromised populations [28]. In addition, access to a high number of clinical covariates allowed exploration of a predictive tool to quantify IFD-risk at the patient-level informed by a range of risk-factors elucidated on multivariate regression analysis. We identified periods of high-risk for IFD from the time of HM diagnosis with the shortest median time seen in AML-patients (3-months) and the longest in patients with MM (22-months). The latter finding reflects the cumulative immunosuppression associated with successive lines of therapy, including immunomodulatory chemotherapies and prolonged corticosteroid exposure that is characteristic of myeloma treatment [29]. Consistent with intervals of high-risk described in Hammond et al. [30], risk-periods of IFD for other HMs were defined including ALL (5-months) and NHL (6-months) [20]. The shorter median time to IFD-onset after transplantation among GVHD-positive- (1-month) compared to GVHD-negative-HSCT-recipients (6-months) reflects the increased immunosuppression associated with GVHD and its treatment [31] (Additional file 5).

During the study period, there was an overall decreasing trend in IFD incidence in Victoria. The 0.28% decline in IFD incidence from 2005-2016, is contrary to the overall 3.5% increase observed in an earlier retrospective study from 1995–1999 [4]. This progressive decrease in IFD incidence is likely multifactorial and related to improved supportive care encompassing broad-spectrum antifungal prophylactic regimens for some subgroup of patients (e.g. AML, HSCT-recipients with GVHD), coupled with improved diagnostic investigations [32], clinical guidelines for IFD [33], better management of GVHD [34], cytomegalovirus prevention [27] and the introduction of high-efficiency particulate air filtration systems into some transplantation wards [35]. While an intensive diagnostic approach incorporating non-culture-based tests increases diagnostic yield [36] and corresponding fungal incidence, their availability is limited with only 35% of centres in a national Australian survey providing on-site Aspergillus galactomannan (GM) or polymerase chain reaction (PCR) diagnostic tests. Therefore, it seems likely that the decline in IFD incidence we observed may be explained by the uptake of mould-active prophylaxis targeting high-risk groups, as seen in a major Victorian transplant centre, which reported a reduction in IFD incidence in patients with AML from 25% with fluconazole use to 3% with posaconazole use over a 12-year period [37]. Indeed, this practice is widespread, with a nationwide survey reporting that posaconazole prophylaxis was used in 90% of AML patients undergoing chemotherapy and 68% of allogeneic-HSCT recipients, with lower rates among ALL patients of 53% [38], highlighting the lack of a standardised approach in this patient group. Consistent with the 5.7% increase in IA incidence during the warmer months as reported by Panackal et al. [39], the peaks in IFD incidence at the onset of spring indicates seasonality not previously described in the southern hemisphere (Fig. 5). This knowledge could ensure that preventative strategies, coupled with enhanced surveillance, also take seasonality into consideration.

Linkage of administrative and clinical datasets could potentially improve knowledge discovery for a rare disease such as IFD, but is contingent on the completeness of hospital-level data collection. Cancer surveillance systems that leverage data linkage between the VCR and clinical registries is considered a technological solution to more accurately determine the epidemiology of rare leukaemia in Victoria [40]. Limited international [14] and Australian data [15] suggest that IFD are under-reported in hospital administrative systems. This is in a large part because fungal surveillance is difficult requiring multidisciplinary input followed by adjudication of cases according to complex definitions [41]. Chang et al. described the poor sensitivity of coding data of 32% for proven/probable IA in HSCT-recipients and its poor positive predictive value of 15% [14]. However, the quality of coding practice is dependent on the quality of medical record documentation, particularly discharge summaries and this has been shown to be suboptimal for IFD even when fungaemia was present [15]. Institutional underreporting has implications for hospital reimbursement but also diminishes the utility of large datasets for rare disease surveillance. Furthermore, the fact that no HSCT-recipient with an IFD was admitted to the ICU in our study is implausible considering that patients with mucormycosis frequently have multiple surgeries and require ICU support (Table 1) [6]. The introduction of sensitive machine learning-based data analytics [42] could enable real-time surveillance of IFD and improve the quality of fungal reporting at the hospital level where most of these infections are managed.

There are several limitations to this study. The quality of coding data for IFD is the foremost consideration as previously discussed. Linkage of the VAED with the VCR was only available between the 1^st January 2008 and the 31^st December 2014. Thus, we relied on the VAED to identify index hospitalisations for the other years without verification against confirmed HM-diagnosis from the VCR. Secondly, as a retrospective study, our analysis is subject to misclassification or miscoding of IFD [14]. Finally, the risk-factors we identified from multivariate analysis require validation against a separate dataset, but large datasets for IFD are currently unavailable due to the lack of comprehensive surveillance systems.

The true burden of IFD among haematology-oncology patients is difficult to accurately determine from hospital-based data. We hypothesise that the true incidence is likely to be higher but without implementation of surveillance systems, it will remain underestimated. The migration of hospital systems both within Victoria, and globally, to the electronic medical record provides an opportunity to improve IFD surveillance through innovative data mining techniques [42].