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Pour limiter la propagation de la maladie à coronavirus 2019 (COVID-19), de nombreux pays ont décidé de réduire le nombre d’interventions chirurgicales non urgentes, ce qui a créé des retards en chirurgie partout dans le monde. Notre objectif était d’évaluer l’ampleur du retard pour ce type d’interventions en Ontario, au Canada, ainsi que le temps et les ressources nécessaires pour y remédier. Nous avons consulté 6 bases de données administratives décrivant la population ontarienne et canadienne pour dégager la distribution du volume chirurgical et de la cadence des salles d’opération pour chaque type d’interventions et chaque région, et connaître la durée d’occupation d’un lit d’hôpital et d’un lit de soins intensifs. Les données utilisées concernent l’ensemble ou une partie de la période du 1er janvier 2017 au 13 juin 2020. Nous avons estimé l’ampleur du retard accumulé et prédit le temps nécessaire pour le reprendre dans un scénario avec capacité d’appoint de + 10 % (ajout d’un jour à 50 % de la capacité par semaine) à l’aide de modèles de séries chronologiques, de modèles de files d’attente et d’une analyse de sensibilité probabiliste. Entre le 15 mars et le 13 juin 2020, le retard en chirurgie à l’échelle de l’Ontario s’est accru de 148 364 opérations (intervalle de prévision à 95 % 124 508–174 589) au total, et en moyenne de 11 413 opérations par semaine. Pour reprendre le retard accumulé, il faudra environ 84 semaines (intervalle de confiance [IC] à 95 % 46–145) et une cadence hebdomadaire de 717 patients (IC à 95 % 326–1367), qui elle demande 719 heures passées au bloc opératoire (IC à 95 % 431–1038), 265 lits d’hôpital (IC à 95 % 87–678) et 9 lits de soins intensifs (IC à 95 % 4–20) par semaine. L’ampleur du retard en chirurgie dû à la COVID-19 laisse entrevoir de graves conséquences pour la phase de reprise en Ontario. Le cadre qui nous a servi à modéliser la reprise du retard peut être adapté ailleurs, avec des données locales, pour faciliter la planification.

To mitigate the effects of coronavirus disease 2019 (COVID-19), jurisdictions worldwide ramped down nonemergent surgeries, creating a global surgical backlog. We sought to estimate the size of the nonemergent surgical backlog during COVID-19 in Ontario, Canada, and the time and resources required to clear the backlog. We used 6 Ontario or Canadian population administrative sources to obtain data covering part or all of the period between Jan. 1, 2017, and June 13, 2020, on historical volumes and operating room throughput distributions by surgery type and region, and lengths of stay in ward and intensive care unit (ICU) beds. We used time series forecasting, queuing models and probabilistic sensitivity analysis to estimate the size of the backlog and clearance time for a +10% (+1 day per week at 50% capacity) surge scenario. Between Mar. 15 and June 13, 2020, the estimated backlog in Ontario was 148 364 surgeries (95% prediction interval 124 508–174 589), an average weekly increase of 11 413 surgeries. Estimated backlog clearance time is 84 weeks (95% confidence interval [CI] 46–145), with an estimated weekly throughput of 717 patients (95% CI 326–1367) requiring 719 operating room hours (95% CI 431–1038), 265 ward beds (95% CI 87–678) and 9 ICU beds (95% CI 4–20) per week. The magnitude of the surgical backlog from COVID-19 raises serious implications for the recovery phase in Ontario. Our framework for modelling surgical backlog recovery can be adapted to other jurisdictions, using local data to assist with planning.

Background Waiting for procedures delayed by COVID‐19 may cause anxiety and related adverse consequences. Objective To synthesize research on the mental health impact of waiting and patient‐centred mitigation strategies that could be applied in the COVID‐19 context. Methods Using a scoping review approach, we searched 9 databases for studies on waiting lists and mental health and reported study characteristics, impacts and intervention attributes and outcomes. Results We included 51 studies that focussed on organ transplant (60.8%), surgery (21.6%) or cancer management (13.7%). Most patients and caregivers reported anxiety, depression and poor quality of life, which deteriorated with increasing wait time. The impact of waiting on mental health was greater among women and new immigrants, and those of younger age, lower socio‐economic status, or with less‐positive coping ability. Six studies evaluated educational strategies to develop coping skills: 2 reduced depression (2 did not), 1 reduced anxiety (2 did not) and 2 improved quality of life (2 did not). In contrast, patients desired acknowledgement of concerns, peer support, and periodic communication about wait‐list position, prioritization criteria and anticipated procedure date. Conclusions Findings revealed patient‐centred strategies to alleviate the mental health impact of waiting for procedures. Ongoing research should explore how to optimize the impact of those strategies for diverse patients and caregivers, particularly in the COVID‐19 context. Patient or Public Contribution Six patients and four caregivers waiting for COVID‐19‐delayed procedures helped to establish eligibility criteria, plan data extraction and review a draft and final report.

Pathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC) settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS), textural analysis and molecular features in patients with locally advanced breast cancer. The study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF) data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR), partial responders (PR), and non-responders (NR). Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times. Of the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone predicted the three response groups with accuracies less than 60% at all scan time points. Recurrence free survival (RFS) of response groups determined based on combined features followed similar trend as determined based on clinical and pathology. This work demonstrates the potential of using QUS, texture and molecular features for predicting the response of primary breast tumors to chemotherapy early, and guiding the treatment planning of refractory patients.

Background Multidisciplinary Cancer Conferences (MCCs) are prospective meetings involving cancer specialists to discuss treatment plans for patients with cancer. Despite reported gaps in MCC quality, there have been few efforts to improve its functioning. The purpose of this study was to use theoretically-rooted knowledge translation (KT) theories and frameworks to inform the development of a strategy to improve MCC decision-making quality. Methods A multi-phased approach was used to design an intervention titled the KT-MCC Strategy. First, key informant interviews framed using the Theoretical Domains Framework (TDF) were conducted with MCC participants to identify barriers and facilitators to optimal MCC decision-making. Second, identified TDF domains were mapped to corresponding strategies using the COM-B Behavior Change Wheel to develop the KT-MCC Strategy. Finally, focus groups with MCC participants were held to confirm acceptability of the proposed KT-MCC Strategy. Results Data saturation was reached at n  = 21 interviews. Twenty-seven barrier themes and 13 facilitator themes were ascribed to 11 and 10 TDF domains, respectively. Differences in reported barriers by physician specialty were observed. The resulting KT-MCC Strategy included workshops, chair training, team training, standardized intake forms and a synoptic discussion checklist, and, audit and feedback. Focus groups ( n  = 3, participants 18) confirmed the acceptability of the identified interventions. Conclusion Myriad factors were found to influence MCC decision making. We present a novel application of the TDF and COM-B to the context of MCCs. We comprehensively describe the barriers and facilitators that impact MCC decision making and propose strategies that may positively impact the quality of MCC decision making.

To evaluate whether the early identification of patients who may benefit from palliative care impacts on the use of palliative, community and acute-based care services. Between 2014 and 2017, physicians from eight sites were encouraged to systematically identify patients who were likely to die within one year and would were thought to benefit from early palliative care. Patients in the INTEGRATE Intervention Group were 1:1 matched to controls selected from provincial healthcare administrative data using propensity score-matching. The use of palliative care, community-based care services (home care, physician home visit, and outpatient opioid use) and acute care (emergency department, hospitalization) was each evaluated within one year after the date of identification. The hazard ratio (HR) in the Intervention Group was calculated for each outcome. Of the 1,185 patients in the Intervention Group, 951 (80.3%) used palliative care services during follow-up, compared to 739 (62.4%) among 1,185 patients in the Control Group [HR of 1.69 (95% CI 1.56 to 1.82)]. The Intervention Group also had higher proportions of patients who used home care [81.4% vs. 55.2%; HR 2.07 (95% CI 1.89 to 2.27)], had physician home visits [35.5% vs. 23.7%; HR 1.63 (95% CI 1.46 to 1.92)] or had increased outpatient opioid use [64.3% vs. 52.1%); HR 1.43 (95% CI 1.30 to 1.57]. The Intervention Group was also more likely to have a hospitalization that was not primarily focused on palliative care (1.42 (95% CI 1.28 to 1.58)) and an unplanned emergency department visit for non-palliative care purpose (1.47 (95% CI 1.32 to 1.64)). Physicians actively identifying patients who would benefit from palliative care resulted in increased use of palliative and community-based care services, but also increased use of acute care services.

Background Neoadjuvant chemotherapy (NAC) is increasingly used to treat locally advanced breast cancer (LABC). Improved response to NAC correlates with better survival outcomes. The dual purpose of this study is to report recurrence and survival outcomes for LABC patients treated with NAC, surgery and adjuvant radiotherapy and to correlate these outcomes with tumour response after NAC using multiple response assessment methods. Methods All LABC patients treated for curative intent with NAC, surgery, and adjuvant radiotherapy at our institute between January 2009 and December 2014 were included for analysis. NAC was mostly anthracycline and taxane-based; radiotherapy consisted of 50 Gy to the breast/chest wall and regional lymph nodes. Response to NAC was categorized using synoptic pathology reports, modified-RECIST and Chevallier scores. Survival curves were generated by the Kaplan-Meier method and compared using the log-rank test. Results The cohort included 103 patients nearly equally divided between Stage II ( n  = 53) and Stage III ( n  = 50). Rates of locoregional control (LRC), recurrence-free survival (RFS), and overall survival (OS) were 99, 98, and 100% at 1 year and 89, 69 and 77% at 5 years, respectively. Responses to NAC did not correlate with LRC ( p > 0.05 ) but did correlate with RFS and OS ( p < 0.05 ), except that the Chevallier score did not predict RFS ( p = 0.06 ). Using bivariate Cox modeling tumour size before ( p = 0.003 ) and after ( p < 0.001 ) NAC, stage group ( p = 0.05 ), and response assessed by synoptic pathology ( p = 0.05 ), modified-RECIST ( p = 0.001 ), and Chevallier score ( p = 0.015 ) all predicted for RFS. No factors predicted for LRC. Conclusion Pathologic response by all tested methods correlated with improved survival but were not associated with decreased LRC.

ObjectivesWe explored how to improve communication about low-risk lesions including labels, language and other strategies.DesignQualitative description and thematic analysis to examine the transcripts of telephone interviews with patients who had low-risk lesions and physicians; and mapping to Communication Accommodation Theory to interpret themes.SettingCanadaParticipants15 patients: 6 (40%) bladder, 5 (33%) prostate and 4 (27%) cervix lesions; and 13 physicians: 7 (54%) cervix, 3 (23%) bladder and 3 (23%) prostate lesions.Main outcome measuresPatient and physician views of labels, language and other strategies to improve communication about low-risk lesions.ResultsPatients and clinicians held discordant views about low-risk lesion label impact, preferences and rationale. All labels prompted confusion and anxiety among patients. In contrast, physicians perceived that patients understood that labels they used across all label categories (abnormal, precursor-to-cancer and cancer) implied low risk for cancer progression. Patients preferred abnormal cells, particularly when first learning of their diagnosis, and desired additional information to distinguish their diagnosis from cancer and justify treatment. In contrast, physicians favoured precursor-to-cancer and cancer labels out of habit, to match labels that patients saw elsewhere (online, charts) and to convince patients to attend follow-up and treatment visits. However, patients and physicians largely agreed on the need for 16 strategies that could improve communication about low-risk lesions including language (eg, plain language, situate low-risk lesions on cancer spectrum) and complementary communication strategies (eg, longer appointments, visual aids, connect patients with support services or groups).ConclusionsThe findings build on prior research by revealing that modifying labels is not the only or best strategy needed to improve communication about low-risk lesions. Ongoing research should examine how best to implement the strategies recommended by patients and physicians.

IntroductionPatient-centred care is valued by patients and providers. As management of cancer becomes increasingly complex, the value of providing care that incorporates an individual’s values and preferences along with demographic and tumour factors is increasingly important. To improve care, patients with cancer need easily accessible information on the outcomes important to them. The patient-centred outcome, days at home (DAH), is based on a construct that measures the time a patient spends alive and out of hospitals and healthcare institutions. DAH is accurately measured from various data sources and has shown construct validity with many patient-centred outcomes. There is significant heterogeneity in terms used and definitions for DAH in cancer care. This scoping review aims to consolidate information on the outcome DAH in cancer care and to review definitions and terms used to date to guide future use of DAH as a patient-centred care, research and policy tool.Methods and analysisThis scoping review protocol has been designed with joint guidance from the JBI Manual for Evidence Synthesis and the expanded framework from Arksey and O’Malley. We will systematically search MEDLINE, Embase and Scopus for studies measuring DAH, or equivalent, in the context of active adult cancer care. Broad inclusion criteria have been developed, given the recent introduction of DAH into cancer literature. Editorials, opinion pieces, case reports, abstracts, dissertations, protocols, reviews, narrative studies and grey literature will be excluded. Two authors will independently perform full-text selection. Data will be extracted, charted and summarised both qualitatively and quantitively.Ethics and disseminationNo ethics approval is required for this scoping review. Results will be disseminated through scientific publication and presentation at relevant conferences.

INTERPRETATION : L'ampleur du retard en chirurgie du a la COVID-19 laisse entrevoir de graves consequences pour la phase de reprise en Ontario. Le cadre qui nous a servi a modeliser la reprise du retard peut etre adapte ailleurs, avec des donnees locales, pour faciliter la planification.