Comparison of Cancer Survival Trends in Hungary in the Periods 2001-2005 and 2011-2015 According to a Population-Based Cancer Registry.

Background: Assessment of population-based cancer survival may provide the most valuable feedback about the effectiveness of oncological surveillance and treatment. Aims: Based on the database of the Hungarian National Cancer Registry, standardized incidence rates of lung, breast, colorectal, prostate and cervical cancer were compared to standardized mortality data of the Hungarian Central Statistical Office in the period between 2001 and 2015. Then survival analysis was performed on cleansed database. Results: The incidence of colorectal, breast and prostate cancer increased, while standardized rates of lung and cervical cancer declined. The survival of colorectal, breast and prostate cancer showed improvement. Contrarily, lung cancer exhibited a mild decline, while that of cervical cancer did not change significantly. In earlier stages survival was improved among almost every studied tumor type, while in advanced stages improvement was not observed. Comparison of stage distribution revealed that in the 2011-2015 period colorectal, breast and prostate cancer cases were diagnosed at earlier stages, while lung and cervical cancer patients were typically discovered at more advanced stages. Discussion: The outcome of advanced cancer treatments is better in earlier stages, which highlighted the importance of screening network. However, growth of oncological treatment costs with longer patient survival imposes a constantly increasing burden on society.

Multi-level process mining methodology for exploring disease-specific care processes.

BACKGROUND: Public healthcare is a complex domain with many actors and highly variable protocols, which makes traditional process mining tools less effective and calls for specialized methods. AIM: The objective of the work was to develop a generally applicable process mining methodology to explore care processes related to diseases. METHODS: The proposed methodology called Process Mining Methodology for Exploring Disease-specific Care Processes (MEDCP) is based on a systematic, step-wise refinement of the raw event logs by using such a multi-level expert taxonomy of events that encapsulates the professional concepts of the analysis. A treatment process is defined according to domain-specific rules to identify the starting (index) and closing events. Concepts from various levels of the taxonomy support the final process definition for an analysis that can deliver meaningful conclusions for domain experts. RESULTS: The applicability of the methodology was demonstrated on two case studies in the cardiological and oncological care domains, in the public health care system in Hungary over a period of ten years. Thanks to the multi-level taxonomy, these studies successfully identified the most important high-level event sequence patterns and some key anomalies in the national care system, such as the significantly different behavior of low-volume vs. high volume care providers in the oncology study or the geographically connected, homogeneous clusters of providers with similar care spectra in the cardiology study. DISCUSSION: As the case studies showed, the proposed methodology can improve the efficiency of standard process mining methods, and deliver high level conclusions that are easy to interpret by domain experts. System-level insight into health care processes can serve as a basis for the optimisation and long-term planning of the whole care system.

Preventing cancer therapy-related heart failure: the need for novel studies.

AIMS: After enhancing the survivorship of cancers, the impact of cardiovascular diseases on mortality is increasing among cancer patients. However, anticancer therapies pose a higher cardiovascular risk to patients. As prevention against cancer therapy-induced cardiomyopathy has yet to be explored, the preventive ability of concomitant cardiovascular medications against incident heart failure was assessed. METHODS: A retrospective, population-based study was run using anonymized integration of healthcare databases. All the Hungarian patients diagnosed with breast or colorectal carcinoma and undergoing chemotherapy or biological therapy were analysed. Participants were not treated with any anticancer therapy nor suffered from heart failure/dilated cardiomyopathy during the preceding observational period (≥6.5 years). The heart failure endpoint was established by I50 International Classification of Diseases codes upon discharge from hospital or issuance of an autopsy report. RESULTS: Among the 9575 patients who were enrolled, the cumulative incidence of heart failure over 4 years was 6.9%. The time until the first heart failure event in the propensity score-matched treated and untreated groups was compared using Cox proportional-hazards models. A significant association between lower heart failure risk and concomitant statin therapy was observed (hazard ratio: 0.748, P = 0.038); the preventive ability was more pronounced in the anthracycline/capecitabine/platinum-treated subgroup (hazard ratio: 0.660, P = 0.032). For angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker therapy, a significantly lower heart failure risk was also observed (hazard ratio: 0.809, P = 0.032). Among beta blockers, nebivolol administered to anthracycline/capecitabine-treated patients was associated with a nonsignificant trend to lower heart failure risk (hazard ratio: 0.584, P = 0.069). CONCLUSION: Only concomitant statin and angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker therapies were associated with significantly lower risk of anticancer therapy-related heart failure.

Risk prediction model for long-term heart failure incidence after epirubicin chemotherapy for breast cancer - A real-world data-based, nationwide classification analysis.

BACKGROUND: Dilated cardiomyopathy (DCM) incidence during and after anthracycline therapy is highly dependent on anthracycline cumulative dose (CD), but its detailed risk factors remained unexplored. Our aim was to assess heart failure (HF) incidence after epirubicin therapy and construct a HF risk-prediction score. METHODS AND RESULTS: A retrospective study was conducted by anonymized integration of nationwide healthcare databases. All the analysed patients were diagnosed with breast carcinoma confirmed by histology from 2007 to 2016. Participants did not undergo chemo- or radiotherapy or suffer HF/DCM during the preceding 3 years. The HF endpoint was established by assignment of I50 International Classification of Diseases (ICD) codes upon discharge from hospital or issuance of an autopsy report. 8068 patients treated with epirubicin were analysed. The 3-10-year HF cumulative incidence was 6.9%. Using binomial logistic regression the independent predictors were identified. A CD-dependent and significant effect on HF was revealed for epirubicin (threshold dose: 709 mg/m2, odds ratio (OR): 1.76) and docetaxel (CD: >510 mg/m2, OR: 1.59; CD ≤510 mg/m2, OR: 1.28, respectively). HF risk increased with age, even over 40. A risk-prediction score derived from regression coefficients consisting of age, diabetes mellitus, hypertension, coronary artery disease, stroke, epirubicin CD, docetaxel CD, capecitabine, gemcitabine, bevacizumab and cancer stage was able to classify HF risk over a wide range (2-30%). CONCLUSION: Long-term HF risk for patients treated with epirubicin was stratified by our risk-prediction score with a nearly 15-fold difference between the lowest and highest groups.

Frequent Treatment Sequence Mining from Medical Databases.

The huge amount of data stored in healthcare databases allows wide range possibilities for data analysis. In this article, we present a novel multilevel analysis methodology to generate and analyze sequential healthcare treatment events. The event sequences can be generated on different abstraction levels automatically from the source data, and so they describe the treatment of patients on different levels of detail. To present applicability of the proposed methodology, we introduce a short case study as well, in which some analysis results are presented arising from the analysis of a group of patients suffering from colorectal cancer.