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With the declaration of the global pandemic, surgical slowdowns were instituted to conserve health care resources for anticipated surges in patients with COVID-19. The long-term implications on survival of these slowdowns for patients with cancer in Canada is unknown. We constructed a microsimulation model based on real-world population data on cancer care from Ontario, Canada, from 2019 and 2020. Our model estimated wait times for cancer surgery over a 6-month period during the pandemic by simulating a slowdown in operating room capacity (60% operating room resources in month 1, 70% in month 2, 85% in months 3–6), as compared with simulated prepandemic conditions with 100% resources. We used incremental differences in simulated wait times to model survival using per-day hazard ratios for risk of death. Primary outcomes included life-years lost per patient and per cancer population. We conducted scenario analyses to evaluate alternative, hypothetical scenarios of different levels of surgical slowdowns on risk of death. The simulated model population comprised 22 799 patients waiting for cancer surgery before the pandemic and 20 177 patients during the pandemic. Mean wait time to surgery prepandemic was 25 days and during the pandemic was 32 days. Excess wait time led to 0.01–0.07 life-years lost per patient across cancer sites, translating to 843 (95% credible interval 646–950) life-years lost among patients with cancer in Ontario. Pandemic-related slowdowns of cancer surgeries were projected to result in decreased long-term survival for many patients with cancer. Measures to preserve surgical resources and health care capacity for affected patients are critical to mitigate unintended consequences.

Background The COVID-19 pandemic greatly impacted primary care and cancer care. We studied how primary care utilization in Ontario, Canada changed for patients who were newly diagnosed with cancer just prior to the COVID-19 pandemic compared to those diagnosed in non-pandemic years. Methods This population-based, retrospective cohort study used linked healthcare databases to compare outcomes for patients with a new malignancy diagnosed within the year prior to the COVID-19 pandemic, between July 1 and September 30, 2019 (COVID-19 cohort) to those diagnosed in the same months in 2018 and 2017 (pre-pandemic cohort). We used Poisson regression models to compare rates of in-person and virtual visits to patients’ usual primary care physician (PCP), emergency department (ED) visits, and hospitalizations, all reported per person-year of follow-up. Results In-person visits to usual PCPs decreased from 4.07/person-year in the pre-pandemic cohort to 2.58 in the COVID-19 cohort ( p  < 0.0001). Virtual visits to usual PCPs increased from 0.00 to 1.53 ( p  < 0.0001). Combined in-person and virtual visits to patients’ usual PCPs was unchanged from 4.07 to 4.12 ( p  = 0.89). The rate of ED visits decreased from 0.99/person-year to 0.88 ( p  < 0.0001). Non-elective hospitalizations remained unchanged, from 0.49/person-year to 0.47 ( p  = 0.1675). Conclusion There was a sizeable shift in primary care visits for cancer patients from in-person to virtual during the pandemic, although there was no resultant increase in hospitalizations. This suggests that early in the pandemic, virtual care allowed for continuity in utilization of primary care, though further studies are required to confirm this persisted later in the pandemic.

Background For novel cancer treatments, effectiveness in clinical practice is not always aligned with clinical efficacy results. As such it is important to understand a treatment’s real-world effectiveness. We examined real-world population-based comparative effectiveness of second-line ipilimumab versus non-ipilimumab treatments (chemotherapy or targeted treatments). Methods We used a cohort of melanoma patients receiving systemic treatment for advanced disease since April 2005 from Ontario, Canada. Patients were identified from provincial drug databases and the Ontario Cancer Registry who received second-line ipilimumab from 2012 to 2015 (treated) or second-line non-ipilimumab treatment prior to 2012 (historical controls). Historical controls were chosen, to permit the most direct comparison to pivotal trial findings. The cohort was linked to administrative databases to identify baseline characteristics and outcomes. Kaplan-Meier curves and multivariable Cox regression models were used to assess overall survival (OS). Observed potential confounders were adjusted for using inverse probability of treatment weighting (IPTW). Results We identified 329 patients with metastatic melanoma (MM) who had received second-line treatments (189 treated; 140 controls). Patients receiving second-line ipilimumab were older (61.7 years vs 55.2 years) compared to historical controls. Median OS were 6.9 (95% CI: 5.4–8.3) and 4.95 (4.3–6.0) months for ipilimumab and controls, respectively. The crude 1-year, 2-year, and 3-year OS probabilities were 34.3% (27–41%), 20.6% (15–27%), and 15.2% (9.6–21%) for ipilimumab and 17.1% (11–23%), 7.1% (2.9–11%), and 4.7% (1.2–8.2%) for controls. Ipilimumab was associated with improved OS (IPTW HR = 0.62; 95% CI: 0.49–0.78; p  < 0.0001). Conclusions This real-world analysis suggests second-line ipilimumab is associated with an improvement in OS for MM patients in routine practice.

Cancer treatment details (i.e., radiation site, chemotherapy dose) are required to conduct rigorous health services research but are difficult to obtain from administrative data. We conducted a validation study to ascertain the optimal algorithm for defining cancer treatment details in cancer-specific and general health administrative data using available chart-abstracted data from adolescent and young adult (AYA) cancer patients. Health administrative data and cancer treatment data reported by visit in Ontario, Canada were compared separately and in a combined algorithm to a reference-standard chart-abstracted database of AYA cancer patients diagnosed in 2005–2012 (n = 1173). We tested algorithms for three tiers of treatment details: any chemotherapy/radiotherapy provided; type of chemotherapy/site of radiation; dose of chemotherapy/radiation. For each algorithm, we calculated sensitivity, specificity, positive predictive value, negative predictive value with 95 % confidence intervals (95 %CI) and simple kappa statistics, overall and according to cancer type, diagnosis period, and locus of care. General health administrative data had high sensitivity and specificity (> 80 %) for detection of any chemotherapy (n = 942) or radiation exposure (n = 412) and was not improved by using cancer-specific data. In 475 patients (40.5 %) with chemotherapy treatment records, sensitivity (22.4–59.6 %) and specificity (95.8–99.1 %) varied by chemotherapy type/class. Factors associated with missing records include locus of care (9.5 % in pediatric vs. 81.7 % in adult cancer centres), year of diagnosis, and type of cancer. There was moderate to strong correlation (r = 0.50–0.79) between dosing for the most common anthracyclines, combined alkylators, cisplatin, and bleomycin. For radiation treatment data (n = 406, 98.5 %), sensitivity and specificity for radiation site ranged from 73.4 % to 91.2 % and 96.6 % to 99.7 %, respectively, with strong dosing correlation (r = 0.63–0.95, by site). Both general and cancer-specific health administrative data have value in determining receipt of chemotherapy and/or radiation and can be used reliably to create cohorts of exposed cancer patients. More granular information regarding dose and type of chemotherapy and dose and site of radiation therapy is highly specific but limited by variable sensitivity. Care should be taken when using the data to estimate prevalence, compare treated/untreated groups or when full capture of an exposed population is otherwise required as underestimations of the true effect may occur. •Identifying cancer therapy details using administrative data has multiple uses.•General health administrative data accurately captures treatment modality.•Our validation shows that specific agent and dose requires cancer-specific data.•These data can reliably be used to create cohorts to study acute and late effects.

Purpose Palonosetron, a 5-hydroxytryptamine 3 receptor antagonist (5-HT 3 RA) with a strong binding affinity and long half-life, has been used in numerous trials for the prophylaxis of chemotherapy-induced nausea and vomiting (CINV). We systematically reviewed the efficacy and safety of palonosetron compared to other 5-HT 3 RAs in CINV prophylaxis. Methods A literature search of Ovid MEDLINE, EMBASE, and CENTRAL was conducted to identify randomized controlled trials (RCTs) comparing palonosetron to other 5-HT 3 RAs in CINV prophylaxis. Primary endpoints were the percentage of patients achieving a complete response (CR), complete control (CC), no emesis, no nausea, or taking no rescue medications. Secondary endpoints were the percentage of patients suffering from 5-HT 3 RA-related adverse events. Results Sixteen RCTs were identified with 2,896 patients randomized to palonosetron and 3,187 patients randomized to other 5-HT 3 RAs. Palonosetron was consistently statistically superior in CR, CC, no emesis, or no nausea and was sometimes superior in no rescue medication. Subgroup analyses demonstrated similarity in efficacy between highly and moderately emetogenic chemotherapy cohorts. In the acute phase, statistical superiority of palonosetron was found for trials that did not allow dexamethasone; conversely, RCTs that administered dexamethasone to all patients were nonsignificant. Palonosetron was statistically significantly safer in dizziness and mean QTc interval change and similar in constipation, headache, and diarrhea. Clinical superiority of palonosetron was reached in 3 of 19 analyzed efficacy and safety endpoints. Conclusions Palonosetron is safer and more efficacious than other 5-HT 3 RAs. Future antiemetic guidelines should discuss the merits of including palonosetron as a first-line treatment.

Background Traditionally, economic evaluations have engaged clinicians and policymakers; however, patients and their caregivers have insight that can ensure that the economic evaluation process appropriately reflects disease consequences and adequately addresses their priorities related to treatment. Objective We aimed to identify patient priorities to inform an early economic evaluation of chimeric antigen receptor T-cell therapy for adults with relapsed or refractory B-cell acute lymphoblastic leukemia. Methods We conducted two online group discussions of four participants each, involving patients with experience of hematological cancer and a caregiver. We used an adapted version of the nominal group technique, a consensus-building discussion approach, to generate focused qualitative data. Results Patients and a caregiver acknowledged both the costs directly related to clinical care, such as the out-of-pocket cost of drugs, and the indirect treatment costs, such as the cost of transport, accommodation, and food. The emotional and physical toll of treatment and the influence of treatment on employment and education were additional costs emphasized by participants. Treatment benefits prioritized by participants included the efficacy of treatment, manageable side effects, improved quality of life, accessibility of treatment, and short treatment duration. Conclusions Engaging patients and caregivers in an early economic evaluation could help identify additional costs and benefits of therapies that are not typically recognized in economic evaluations but have the potential to increase the commercial viability of novel therapies. This research also demonstrates how patients and caregivers can be engaged at different levels in the development of early economic evaluation models.

Patients with small-cell lung cancer (SCLC) are at high risk for intracranial metastatic disease (IMD). Although stereotactic radiosurgery (SRS) has supplanted whole brain radiotherapy (WBRT) as first-line treatment for IMD in most solid cancers, WBRT remains first-line treatment for IMD in patients with SCLC. We aimed to evaluate the efficacy of SRS in comparison with WBRT and assess treatment outcomes following SRS. In this systematic review and meta-analysis, we searched MEDLINE, Embase, CENTRAL, and grey literature sources for controlled trials and cohort studies published in English reporting on SRS for IMD treatment in patients with SCLC from inception to March 23, 2022. Studies were excluded that did not report on SRS for IMD secondary to SCLC. Summary data were extracted. The primary outcome was overall survival, presented as pooled hazard ratios (HR) through random-effects meta-analysis for studies comparing SRS with WBRT with or without SRS boost, and as medians for single-arm SRS studies. This study is registered with the Open Science Framework, DOI 10.17605/OSF.IO/8M4HC, and PROSPERO, CRD42021258197. Of 3823 identified records, 31 were eligible for inclusion; seven were included in the meta-analysis. Overall survival following SRS was longer than following WBRT with or without SRS boost (HR 0·85; 95% CI 0·75–0·97; n=7 studies; n=18 130 patients), or WBRT alone (0·77; 0·72–0·83; n=7 studies; n=16 961 patients), but not WBRT plus SRS boost (1·17, 0·78–1·75; n=4 studies; n=1167 patients). Using single-arm studies, pooled median overall survival from SRS was 8·99 months (95% CI 7·86–10·16; n=14 studies; n=1682 patients). Between-study heterogeneity was considerable when pooled among all comparative studies (I2=71·9%). These results suggest survival outcomes are equitable following treatment with SRS compared with WBRT in patients with SCLC and IMD. Future prospective studies should focus on tumour burden and differences in local and distant intracranial progression between WBRT-treated and SRS-treated patients with SCLC. None.

BackgroundPatients with cancer may be at increased risk of osteoporosis and fracture; however, gaps exist in the existing literature and the association between cancer and fracture requires further examination.MethodsWe conducted a population-based cohort study of Ontario patients with cancer (breast, prostate, lung, gastrointestinal, haematologic) diagnosed between January 2007 to December 2018 and 1:1 matched non-cancer controls. The primary outcome was incident fracture (end of follow-up December 2019). Multivariable Cox regression analysis was used to estimate the relative fracture risk with sensitivity analysis accounting for competing risk of death.ResultsAmong 172,963 cancer patients with non-cancer controls, 70.6% of patients with cancer were <65 years old, 58% were female, and 9375 and 8141 fracture events were observed in the cancer and non-cancer group, respectively (median follow-up 6.5 years). Compared to non-cancer controls, patients with cancer had higher risk of fracture (adjusted HR [aHR] 1.10, 95% CI 1.07–1.14, p < 0.0001), which was also observed for both solid (aHR 1.09, 95% CI 1.05–1.13, p < 0.0001) and haematologic cancers (aHR 1.20, 95% CI 1.10–1.31, p < 0.0001). Sensitivity analysis accounting for competing risk of death did not change these findings.ConclusionsOur study indicates that patients with cancer are at modest risk of fractures compared to non-cancer controls.

Purpose In the past decade, literature has called attention to financial toxicities experienced by cancer patients. Though studies have addressed research questions in high-income countries, there remains a paucity of in-depth reviews regarding low- and middle-income countries (LMICs). Our scoping review provides an overview of treatment-related financial toxicities experienced by cancer patients in LMICs. Methods A systematic search was conducted in MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials. English peer-reviewed articles that (a) explored patients’ experience with financial toxicity due to cancer treatment (b) were specific to LMICs as defined by the World Bank and (c) focused on qualitative data were included. Details regarding participants and main findings were extracted and synthesized. Results The search yielded 6290 citations, and 42 studies across 3 low-income, 9 lower-middle-income and 8 upper-middle-income countries. Main themes identified included cancer patients encountered various material hardships, managed costs with different coping behaviours and experienced negative psychological responses to their financial burden. Higher levels of financial toxicities were associated with patient characteristics such as lower socio-economic status and lack of insurance, as well as patient outcomes such as lower quality of life. Conclusion Cancer patients in LMIC experience deleterious financial toxicities as a result of treatment. This comprehensive characterization of financial toxicities will better allow health systems to adopt evidence-based mitigation strategies to reduce the financial burden on patients.

Background Cancer is a major public health issue and represents a significant economic burden to health care systems worldwide. The objective of this analysis was to estimate phase-specific, 5-year and lifetime net costs for the 21 most prevalent cancer sites, and remaining tumour sites combined, in Ontario, Canada. Methods We selected all adult patients diagnosed with a primary cancer between 1997 and 2007, with valid ICD-O site and histology codes, and who survived 30 days or more after diagnosis, from the Ontario Cancer Registry ( N  = 394,092). Patients were linked to treatment data from Cancer Care Ontario and administrative health care databases at the Institute for Clinical and Evaluative Sciences. Net costs (i.e., cost difference between patients and matched non-cancer control subjects) were estimated by phase of care and sex, and used to estimate 5-year and lifetime costs. Results Mean net costs of care (2009 CAD) were highest in the initial (6 months post-diagnosis) and terminal (12 months pre-death) phases, and lowest in the (3 months) pre-diagnosis and continuing phases of care. Phase-specific net costs were generally lowest for melanoma and highest for brain cancer. Mean 5-year net costs varied from less than $25,000 for melanoma, thyroid and testicular cancers to more than $60,000 for multiple myeloma and leukemia. Lifetime costs ranged from less than $55,000 for lung and liver cancers to over $110,000 for leukemia, multiple myeloma, lymphoma and breast cancer. Conclusions Costs of cancer care are substantial and vary by cancer site, phase of care and time horizon analyzed. These cost estimates are valuable to decision makers to understand the economic burden of cancer care and may be useful inputs to researchers undertaking cancer-related economic evaluations.