Background:
The COVID-19 pandemic impacted cancer diagnosis and treatment. However, little is known about end-of-life cancer care during the pandemic.
Aim:
To investigate potentially inappropriate ...end-of-life hospital care for cancer patients before and during the COVID-19 pandemic.
Design:
Retrospective population-based cohort study using data from the Netherlands Cancer Registry and the Dutch National Hospital Care Registration. Potentially inappropriate care in the last month of life (chemotherapy administration, >1 emergency room contact, >1 hospitalization, hospitalization >14 days, intensive care unit admission or hospital death) was compared between four COVID-19 periods and corresponding periods in 2018/2019.
Participants:
A total of 112,919 cancer patients (⩾18 years) who died between January 2018 and May 2021 were included.
Results:
Fewer patients received potentially inappropriate end-of-life care during the COVID-19 pandemic compared to previous years, especially during the first COVID-19 peak (22.4% vs 26.0%). Regression analysis showed lower odds of potentially inappropriate end-of-life care during all COVID-19 periods (between OR 0.81; 95% CI 0.74–0.88 and OR 0.92; 95% CI 0.87–0.97) after adjustment for age, sex and cancer type. For the individual indicators, fewer patients experienced multiple or long hospitalizations, intensive care unit admission or hospital death during the pandemic.
Conclusions:
Cancer patients received less potentially inappropriate end-of-life care during the COVID-19 pandemic. Because several factors may have contributed, it is unclear whether this reflects better quality care. However, these findings raise important questions about what pandemic-induced changes in care practices can help provide appropriate end-of-life care for future patients in the context of increasing patient numbers and limited resources.
During the COVID-19 pandemic cancer patients might have experienced delays in screening, diagnosis and/or treatment. A systematic review was conducted to give an overview of the effects of COVID-19 ...induced delays in oncological care on the physical and mental health outcomes of cancer patients.
MEDLINE and EMBASE databases were searched for articles on the effects of COVID-19 induced delays on physical and mental health outcomes.
Out of 1333 papers, eighteen observational, and twelve modelling studies were included. In approximately half of the studies, tumor stage distribution differed during the pandemic compared to before the pandemic. Modelling studies predicted that the estimated increase in the number of deaths ranged from -0.04 to 30%, and the estimated reduction in survival ranged from 0.4 to 35%. Varying results on the impact on mental health, e.g. anxiety and depression, were seen.
Due to large methodological discrepancies between the studies and the varying results, the effect of COVID-19 induced delays on the physical and mental health outcomes of cancer patients remains uncertain. While modelling studies estimated an increase in mortality, observational studies suggest that mortality might not increase to a large extent. More longitudinal observational data from the pandemic period is needed for more conclusive results.
Due to the abundant usage of chemotherapy in young triple-negative breast cancer (TNBC) patients, the unbiased prognostic value of BRCA1-related biomarkers in this population remains unclear. In ...addition, whether BRCA1-related biomarkers modify the well-established prognostic value of stromal tumor-infiltrating lymphocytes (sTILs) is unknown. This study aimed to compare the outcomes of young, node-negative, chemotherapy-naïve TNBC patients according to BRCA1 status, taking sTILs into account.
We included 485 Dutch women diagnosed with node-negative TNBC under age 40 between 1989 and 2000. During this period, these women were considered low-risk and did not receive chemotherapy. BRCA1 status, including pathogenic germline BRCA1 mutation (gBRCA1m), somatic BRCA1 mutation (sBRCA1m), and tumor BRCA1 promoter methylation (BRCA1-PM), was assessed using DNA from formalin-fixed paraffin-embedded tissue. sTILs were assessed according to the international guideline. Patients' outcomes were compared using Cox regression and competing risk models.
Among the 399 patients with BRCA1 status, 26.3% had a gBRCA1m, 5.3% had a sBRCA1m, 36.6% had tumor BRCA1-PM, and 31.8% had BRCA1-non-altered tumors. Compared to BRCA1-non-alteration, gBRCA1m was associated with worse overall survival (OS) from the fourth year after diagnosis (adjusted HR, 2.11; 95% CI, 1.18-3.75), and this association attenuated after adjustment for second primary tumors. Every 10% sTIL increment was associated with 16% higher OS (adjusted HR, 0.84; 95% CI, 0.78-0.90) in gBRCA1m, sBRCA1m, or BRCA1-non-altered patients and 31% higher OS in tumor BRCA1-PM patients. Among the 66 patients with tumor BRCA1-PM and ≥ 50% sTILs, we observed excellent 15-year OS (97.0%; 95% CI, 92.9-100%). Conversely, among the 61 patients with gBRCA1m and < 50% sTILs, we observed poor 15-year OS (50.8%; 95% CI, 39.7-65.0%). Furthermore, gBRCA1m was associated with higher (adjusted subdistribution HR, 4.04; 95% CI, 2.29-7.13) and tumor BRCA1-PM with lower (adjusted subdistribution HR, 0.42; 95% CI, 0.19-0.95) incidence of second primary tumors, compared to BRCA1-non-alteration.
Although both gBRCA1m and tumor BRCA1-PM alter BRCA1 gene transcription, they are associated with different outcomes in young, node-negative, chemotherapy-naïve TNBC patients. By combining sTILs and BRCA1 status for risk classification, we were able to identify potential subgroups in this population to intensify and optimize adjuvant treatment.
In the scope of the European Commission Initiative on Breast Cancer (ECIBC) the Monitoring and Evaluation (M&E) subgroup was tasked to identify breast cancer screening programme (BCSP) performance ...indicators, including their acceptable and desirable levels, which are associated with breast cancer (BC) mortality. This paper documents the methodology used for the indicator selection.
The indicators were identified through a multi-stage process. First, a scoping review was conducted to identify existing performance indicators. Second, building on existing frameworks for making well-informed health care choices, a specific conceptual framework was developed to guide the indicator selection. Third, two group exercises including a rating and ranking survey were conducted for indicator selection using pre-determined criteria, such as: relevance, measurability, accurateness, ethics and understandability. The selected indicators were mapped onto a BC screening pathway developed by the M&E subgroup to illustrate the steps of BC screening common to all EU countries.
A total of 96 indicators were identified from an initial list of 1325 indicators. After removing redundant and irrelevant indicators and adding those missing, 39 candidate indicators underwent the rating and ranking exercise. Based on the results, the M&E subgroup selected 13 indicators: screening coverage, participation rate, recall rate, breast cancer detection rate, invasive breast cancer detection rate, cancers > 20 mm, cancers ≤10 mm, lymph node status, interval cancer rate, episode sensitivity, time interval between screening and first treatment, benign open surgical biopsy rate, and mastectomy rate.
This systematic approach led to the identification of 13 BCSP candidate performance indicators to be further evaluated for their association with BC mortality.
The EuroQoL 5-Dimension 5-Level questionnaire (EQ-5D-5L) and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core-30 (EORTC QLQ-C30) are commonly used ...Patient-Reported Outcome Measures (PROMs) for breast cancer. This study assesses and compares the internal responsiveness of the EQ-5D-5L and EORTC QLQ-C30 in Dutch breast cancer patients during the first year post-surgery. Women diagnosed with breast cancer who completed the EQ-5D-5L and EORTC QLQ-C30 pre-operatively (T0), 6 months (T6), and 12 months post-surgery (T12) were included. Mean differences of the EQ-5D-5L and EORTC QLQ-C30 between baseline and 6 months (delta 1) and between baseline and 12 months post-surgery (delta 2) were calculated and compared against the respective minimal clinically important differences (MCIDs) of 0.08 and 5. Internal responsiveness was assessed using effect sizes (ES) and standardized response means (SRM) for both deltas. In total, 333 breast cancer patients were included. Delta 1 and delta 2 for the EQ-5D-5L index and most scales of the EORTC QLQ-C30 were below the MCID. The internal responsiveness for both PROMs was small (ES and SRM < 0.5), with greater internal responsiveness for delta 1 compared to delta 2. The EQ-5D-5L index showed greater internal responsiveness than the EORTC QLQ-C30 Global Quality of Life scale and summary score. These findings are valuable for the interpretation of both PROMs in Dutch breast cancer research and clinical care.
Clinical prediction models are not routinely validated. To facilitate validation procedures, the online Evidencio platform ( https://www.evidencio.com ) has developed a tool partly automating this ...process. This study aims to determine whether semi-automated validation can reliably substitute manual validation.
Four different models used in breast cancer care were selected: CancerMath, INFLUENCE, Predicted Probability of Axillary Metastasis, and PREDICT v.2.0. Data were obtained from the Netherlands Cancer Registry according to the inclusion criteria of the original development population. Calibration (intercepts and slopes) and discrimination (area under the curve (AUC)) were compared between semi-automated and manual validation.
Differences between intercepts and slopes of all models using semi-automated validation ranged from 0 to 0.03 from manual validation, which was not clinically relevant. AUCs were identical for both validation methods.
This easy to use semi-automated validation option is a good substitute for manual validation and might increase the number of validations of prediction models used in clinical practice. In addition, the validation tool was considered to be user-friendly and to save a lot of time compared to manual validation. Semi-automated validation will contribute to more accurate outcome predictions and treatment recommendations in the target population.
Purpose
EUSOMA’s recommendation that “each patient has to be fully informed about each step in the diagnostic and therapeutic pathway” could be supported by guideline-based clinical decision trees ...(CDTs). The Dutch breast cancer guideline has been modeled into CDTs (
www.oncoguide.nl
). Prerequisites for adequate CDT usage are availability of necessary patient data at the time of decision-making and to consider all possible treatment alternatives provided in the CDT.
Methods
This retrospective single-center study evaluated 394 randomly selected female patients with non-metastatic breast cancer between 2012 and 2015. Four pivotal CDTs were selected. Two researchers analyzed patient records to determine to which degree patient data required per CDT were available at the time of multidisciplinary team (MDT) meeting and how often multiple alternatives were actually reported.
Results
The four selected CDTs were indication for magnetic resonance imaging (MRI) scan, preoperative and adjuvant systemic treatment, and immediate breast reconstruction. For 70%, 13%, 97% and 13% of patients, respectively, all necessary data were available. The two most frequent underreported data-items were “clinical M-stage” (87%) and “assessable mammography” (28%). Treatment alternatives were reported by MDTs in 32% of patients regarding primary treatment and in 28% regarding breast reconstruction.
Conclusion
Both the availability of data in patient records essential for guideline-based recommendations and the reporting of possible treatment alternatives of the investigated CDTs were low. To meet EUSOMA’s requirements, information that is supposed to be implicitly known must be explicated by MDTs. Moreover, MDTs have to adhere to clear definitions of data-items in their reporting.
ObjectivesFor oncological care, there is a clear tendency towards centralisation and collaboration aimed at improving patient outcomes. However, in market-based healthcare systems, this trend is ...related to the potential trade-off between hospital volume and hospital competition. We analyse the association between hospital volume, competition from neighbouring hospitals and outcomes for patients who underwent surgery for invasive breast cancer (IBC).Outcome measuresSurgical margins, 90 days re-excision, overall survival.Design, setting, participantsIn this population-based study, we use data from the Netherlands Cancer Registry. Our study sample consists of 136 958 patients who underwent surgery for IBC between 2004 and 2014 in the Netherlands.ResultsOur findings show that treatment types as well as patient and tumour characteristics explain most of the variation in all outcomes. After adjusting for confounding variables and intrahospital correlation in multivariate logistic regressions, hospital volume and competition from neighbouring hospitals did not show significant associations with surgical margins and re-excision rates. For patients who underwent surgery in hospitals annually performing 250 surgeries or more, multilevel Cox proportional hazard models show that survival was somewhat higher (HR 0.94). Survival in hospitals with four or more (potential) competitors within 30 km was slightly higher (HR 0.97). However, this effect did not hold after changing this proxy for hospital competition.ConclusionsBased on the selection of patient outcomes, hospital volume and regional competition appear to play only a limited role in the explanation of variation in IBC outcomes across Dutch hospitals. Further research into hospital variation for high-volume tumours like the one studied here is recommended to (i) use consistently measured quality indicators that better reflect multidisciplinary clinical practice and patient and provider decision-making, (ii) include more sophisticated measures for hospital competition and (iii) assess the entire process of care within the hospital, as well as care provided by other providers in cancer networks.
To improve Shared decision-making (SDM) regarding personalized post-treatment surveillance, the Breast Cancer Surveillance Decision Aid (BCS-PtDA), integrating personalized risk information, was ...developed and implemented in eight hospitals. The aim of this mixed-methods study was to (1) assess the implementation and participation rates, (2) identify facilitators and barriers for use by health care professionals (HCPs), (3) quantify the observed level of SDM, and (4) evaluate risk communication and SDM application in consultations.
Implementation and participation rates and patients' BCS-PtDA use were calculated using hospital registry data and BCS-PtDA log data. HCPs' perspective on facilitators and barriers were collected using the MIDI framework. Observed SDM levels in consultation transcripts were quantified using the OPTION-5 scale. Thematic analysis was performed to assess consultation content.
The average PtDA implementation and participation rates were, respectively, 26% and 61%. HCPs reported that the PtDA supported choice awareness. Reported barriers for implementation were mainly increased workload and a lack of perceived benefits. The consultation analysis (
= 64) showed patients were offered a choice, but deliberation was lacking. Risk communication was generally adequate.
When the BCS-PtDA was used, patients were clearly given a choice regarding their post-treatment surveillance, but information provision and SDM application can be improved.
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