Delayed treatment in breast cancer patients during the COVID-19 pandemic: a population health information research infrastructure (PHIRI) case study.

BACKGROUND: The indirect impact of the coronavirus disease 2019 pandemic on healthcare services was studied by assessing changes in the trend of the time to first treatment for women 18 or older who were diagnosed and treated for breast cancer between 2017 and 2021. METHODS: An observational retrospective longitudinal study based on aggregated data from four European Union (EU) countries/regions investigating the time it took to receive breast cancer treatment. We compiled outputs from a federated analysis to detect structural breakpoints, confirming the empirical breakpoints by differences between the trends observed and forecasted after March 2020. Finally, we built several segmented regressions to explore the association of contextual factors with the observed changes in treatment delays. RESULTS: We observed empirical structural breakpoints on the monthly median time to surgery trend in Aragon (ranging from 9.20 to 17.38 days), Marche (from 37.17 to 42.04 days) and Wales (from 28.67 to 35.08 days). On the contrary, no empirical structural breakpoints were observed in Belgium (ranging from 21.25 to 23.95 days) after the pandemic's beginning. Furthermore, we confirmed statistically significant differences between the observed trend and the forecasts for Aragon and Wales. Finally, we found the interaction between the region and the pandemic's start (before/after March 2020) significantly associated with the trend of delayed breast cancer treatment at the population level. CONCLUSIONS: Although they were not clinically relevant, only Aragon and Wales showed significant differences with expected delays after March 2020. However, experiences differed between countries/regions, pointing to structural factors other than the pandemic.

Incidence, survival, and mortality of cancer in children and young adolescents in Belgium and the Netherlands in 2004-2015: A comparative population-based study.

International comparisons of cancer surveillance measures may provide insight into inequalities in registration practices, etiological factors, and treatment strategies. This study aimed to compare incidence, survival, and mortality of cancer in children and young adolescents between Belgium and the Netherlands. All children (0-14 years) and young adolescents (15-17 years) diagnosed with cancer between 2004 and 2015 were selected from the population-based cancer registries of Belgium (N = 4739) and the Netherlands (N = 7322). Differences in incidence and mortality were expressed as standardized rate ratios (SRR; BE/NL). Five-year observed survival was calculated using the Kaplan-Meier method. During 2004-2015, the overall cancer incidence among children and young adolescents was similar in both countries. Incidence of neuroblastoma was significantly higher in Belgian children (2010-2015: SRR = 1.3, 95% CI 1.0-1.6). Five-year survival of all malignant cancers was comparable in 2010-2015, exceeding 80% in both age groups. Remarkable differences in survival existed in children for malignant central nervous system (CNS) tumors in 2004-2009 (BE = 62%, NL = 45%), for acute myeloid leukemia (BE = 68%, NL = 78%) and rhabdomyosarcomas (BE = 60%, NL = 79%) in 2010-2015, and for neuroblastoma in both periods (2004-2009: BE = 76%, NL = 64%; 2010-2015: BE = 82%, NL = 64%). Overall cancer mortality in children decreased by approximately 3 percent-points annually in both countries, but was slightly lower in Belgium in 2004-2009 (SRR = 0.9, 95% CI 0.7-1.0). Despite differences for specific cancer types, overall cancer incidence, survival, and mortality were comparable between Dutch and Belgian children and young adolescents in 2010-2015. Variability in screening, diagnosis, and registration practices probably explains the observed differences in incidence and survival of neuroblastoma and malignant CNS tumors.

Epidemiological Trends of Haematological Malignancies in Belgium 2004-2018: Older Patients Show the Greatest Improvement in Survival.

(1) Background: Haematological malignancies (HMs) represent a heterogeneous group of mostly rare cancers that differ in pathophysiology, incidence, and outcome. (2) Methods: Our study aims to understand the epidemiological situation and trends of 24 main types of HMs in Belgium over a 15-year period, with a focus on the impact of age. Age-standardised incidence, average annual percentage change (AAPC), 5- and 10-year relative survival (RS) and RS trends were estimated for all HMs (N = 94,415) diagnosed between 2004 and 2018. (3) Results: Incidence rates of HM increased, mainly in the 70+ age group (AAPC: 3%). RS varied by age and HM type. For each HM type, outcome decreased with age. The greatest decrease with age in 5-year RS is observed for aggressive HM, acute myeloid leukaemia (AML), acute lymphoblastic leukaemia, and Burkitt lymphoma, from 67%, 90%, and 97% below 20 years, to 2%, 12%, and 16% above 80 years of age, respectively. The moderate improvement in 5-year RS over the 2004-2018 period for all HMs, of +5 percentage point (pp), masks highly heterogenous outcomes by HM type and age group. The most impressive improvements are observed in the 80+ group: +45, +33, +28, and +16 pp for Hodgkin lymphoma, immunoproliferative disorders, follicular lymphoma, and chronic myeloid leukaemia, respectively. (4) Conclusions: The increasing incidence and survival over the 2004-2018 period are likely explained by diagnostic and therapeutic innovations, which have spread to populations not targeted by clinical trials, especially older adults. This real-world population-based study highlights entities that need significant improvement, such as AML.

Machine Learning-Based Extraction of Breast Cancer Receptor Status From Bilingual Free-Text Pathology Reports.

As part of its core business of gathering population-based information on new cancer diagnoses, the Belgian Cancer Registry receives free-text pathology reports, describing results of (pre-)malignant specimens. These reports are provided by 82 laboratories and written in 2 national languages, Dutch or French. For breast cancer, the reports characterize the status of estrogen receptor, progesterone receptor, and Erb-b2 receptor tyrosine kinase 2. These biomarkers are related with tumor growth and prognosis and are essential to define therapeutic management. The availability of population-scale information about their status in breast cancer patients can therefore be considered crucial to enrich real-world scientific studies and to guide public health policies regarding personalized medicine. The main objective of this study is to expand the data available at the Belgian Cancer Registry by automatically extracting the status of these biomarkers from the pathology reports. Various types of numeric features are computed from over 1,300 manually annotated reports linked to breast tumors diagnosed in 2014. A range of popular machine learning classifiers, such as support vector machines, random forests and logistic regressions, are trained on this data and compared using their F 1 scores on a separate validation set. On a held-out test set, the best performing classifiers achieve F 1 scores ranging from 0.89 to 0.92 for the four classification tasks. The extraction is thus reliable and allows to significantly increase the availability of this valuable information on breast cancer receptor status at a population level.

Assessing the completeness and correctness of the registration of malignant mesothelioma in Belgium.

OBJECTIVES: Malignant mesothelioma (MM) is a rare and aggressive cancer mostly caused by asbestos exposure, and for which the diagnosis is difficult. This study aimed to assess the completeness and correctness of MM registration using 3 independent national databases: the Belgian Cancer Registry (BCR), the population-based mortality statistics (certificates of death, COD), and the Belgian Mesothelioma Registry (BMR). METHODS: The study cohort included all MM reported to the BCR and diagnosed between 2004 and 2012 (n = 2292), all patients reviewed by the pathology commission of the BMR (2004-2012; n = 2019), and COD data for all Belgian citizens (2004-2013). Available data were compared in terms of registered cases, histological diagnosis, performed immunohistochemical (IHC) tests, and IHC test results. RESULTS: Comparison of BCR with BMR registrations showed 94.8% concordant cases. The proportion of MM diagnoses originally reported to BCR with unspecified MM morphology was reduced from 25.8% to less than 1%. RESULTS: from IHC tests were available for 95.3% of concordant MM cases. Different IHC patterns could be distinguished by MM histology. MM cases registered at BCR for which COD mentioned an MM as underlying cause of death represented 76.4% of deceased cases. MM long-term survivors (survival >3 years; 10.9%) were characterised by distinct clinical and biological characteristics. CONCLUSIONS: A comparison of independent Belgian MM registration databases elucidated under-registration and misclassification and revealed possible reasons for observed discordances. Combining all the available information resulted in enhanced completeness and correctness of MM registration in Belgium and allowed for the identification and characterisation of MM long-term survivors.

A classification prognostic score to predict OS in stage IV well-differentiated neuroendocrine tumors.

No validated prognostic tool is available for predicting overall survival (OS) of patients with well-differentiated neuroendocrine tumors (WDNETs). This study, conducted in three independent cohorts of patients from five different European countries, aimed to develop and validate a classification prognostic score for OS in patients with stage IV WDNETs. We retrospectively collected data on 1387 patients: (i) patients treated at the Istituto Nazionale Tumori (Milan, Italy; n = 515); (ii) European cohort of rare NET patients included in the European RARECAREnet database (n = 457); (iii) Italian multicentric cohort of pancreatic NET (pNETs) patients treated at 24 Italian institutions (n = 415). The score was developed using data from patients included in cohort (i) (training set); external validation was performed by applying the score to the data of the two independent cohorts (ii) and (iii) evaluating both calibration and discriminative ability (Harrell C statistic). We used data on age, primary tumor site, metastasis (synchronous vs metachronous), Ki-67, functional status and primary surgery to build the score, which was developed for classifying patients into three groups with differential 10-year OS: (I) favorable risk group: 10-year OS ≥70%; (II) intermediate risk group: 30% ≤ 10-year OS < 70%; (III) poor risk group: 10-year OS <30%. The Harrell C statistic was 0.661 in the training set, and 0.626 and 0.601 in the RARECAREnet and Italian multicentric validation sets, respectively. In conclusion, based on the analysis of three 'field-practice' cohorts collected in different settings, we defined and validated a prognostic score to classify patients into three groups with different long-term prognoses.

The impact of cancer incidence and stage on optimal utilization of radiotherapy: Methodology of a population based analysis by the ESTRO-HERO project.

BACKGROUND AND PURPOSE: The impact of differences in the distribution of major cancer sites and stages at diagnosis among 4 European countries on the optimal utilization proportion (OUP) of patients who should receive external beam radiotherapy was assessed within the framework of the ESTRO-HERO project. MATERIALS AND METHODS: Data from Australian Collaboration for Cancer Outcomes Research and Evaluation (CCORE) were used. Population based stages at diagnosis from the cancer registries of Belgium, Slovenia, the Greater Poland region of Poland, and The Netherlands were used to assess the OUP for each country. A sensitivity analysis was carried out. RESULTS: The overall OUP by country varied from the lowest of 48.3% in Australia to the highest of 53.4% in Poland; among European countries the variation was limited to 3%. Cancer site specific OUPs showed differences according to the variability in stage at diagnosis across countries. The most important impact on the OUP by country was due to changes in relative frequency of tumours rather than stage at diagnosis. CONCLUSIONS: This methodology can be adapted using European data, thus facilitating the planning of resources required to cope with the demand for radiotherapy in Europe, taking into account the national variability in cancer incidence.

Regional variation in incidence for smoking and alcohol related cancers in Belgium.

The prevalence of life habits may vary substantially within a country. Incidence maps of strongly related diseases can illustrate the distribution of these life style habits. In this study we explored the spatial variation in Belgium for different cancers related to alcohol and/or tobacco. From the Belgian Cancer Registry, municipality specific World Standardised incidence rates for the years 2004-2011 are used to create detailed smoothed cancer maps by subsite or histology for cancers of oral cavity, pharynx, larynx, oesophagus, liver and lung. Cancer incidence is compared both visually (from incidence maps) and with Poisson regression analysis using mortality from chronic liver disease and chronic obstructive pulmonary disease as a proxy for alcohol and tobacco prevalence, respectively. The incidence rates for oral cavity, pharyngeal and laryngeal cancer were comparable with the alcohol gradient. However, glottic cancer revealed a pattern that was more comparable with lung cancer. These two tumour types resembled more closely to the smoking pattern. Oesophageal cancer showed two patterns: squamous cell carcinoma was highly comparable with the background alcohol consumption, while adenocarcinoma was unrelated to one of our two proxies. Our approach and results are an encouraging example how data from a young cancer registry can be used in studies describing the regional cancer burden. The results can be useful for primary prevention to increase awareness for the public, authorities and health care professionals in specific subpopulations.