scholarly journals Clinician participation in CADTH’s pan-Canadian Oncology Drug Review: contribution and impact on cancer drug funding recommendations

2017 ◽  
Vol 24 (2) ◽  
pp. 71
Author(s):  
M. Trudeau ◽  
P. Hoskins ◽  
T. Reiman ◽  
A. Chambers ◽  
H. Mai ◽  
...  
Keyword(s):  
Cancer Drug ◽  
Oncology Drug ◽  
Drug Review

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scholarly journals Impact of the pan-Canadian Oncology Drug Review on provincial concordance with respect to cancer drug funding decisions and time to funding

2017 ◽  
Vol 24 (5) ◽  
pp. 295 ◽  
Author(s):  
A. Srikanthan ◽  
H. Mai ◽  
N. Penner ◽  
E. Amir ◽  
A. Laupacis ◽  
...  
Keyword(s):  
Linear Models ◽  
Drug Product ◽  
Median Number ◽  
Cancer Drug ◽  
Cancer Drugs ◽  
Oncology Drug ◽  
Before And After ◽  
Canadian Provinces ◽  
The Impact ◽  
Drug Review

Background The pan-Canadian Oncology Drug Review (pcodr) was implemented in 2011 to address uneven drug coverage and lack of transparency with respect to the various provincial cancer drug review processes in Canada. We evaluated the impact of the pcodr on provincial decision concordance and time from Notice of Compliance (noc) to drug funding.Methods In a retrospective review, Health Canada’s Drug Product Database was used to identify new indications for cancer drugs between January 2003 and May 2014, and provincial formulary listings for drug-funding dates and decisions between 1 January 2003 and 31 December 2014 were retrieved. Multiple linear models and quantile regressions were used to evaluate changes in time to decision-making before and after the implementation of the pcodr. Agreement of decisions between provinces was evaluated using kappa statistics.Results Data were available from 9 provinces (all Canadian provinces except Quebec), identifying 88 indications that represented 51 unique cancer drugs. Two provinces lacked available data for all 88 indications at the time of data collection. Interprovincial concordance in drug funding decisions significantly increased after the pcodr’s implementation (Brennan-Prediger coefficient: 0.54 pre-pcodr vs. 0.78 post-pcodr; p = 0.002). Nationwide, the median number of days from Health Canada’s noc date to the date of funding significantly declined (to 393 days from 522 days, p < 0.001). Exploratory analyses excluding provinces with incomplete data did not change the results.Conclusions After the implementation of the pcodr, greater concordance in cancer drug funding decisions between provinces and decreased time to funding decisions were observed.

Association between oncology drug review times and public funding recommendations.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 99-99
Author(s):  
Richard Gagnon ◽  
Chelsea Wong ◽  
Eddy Taguedong ◽  
Parthiv Maneesh ◽  
Safiya Karim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Public Funding ◽  
Study Data ◽  
Clinical Indication ◽  
Cancer Drug ◽  
P Value ◽  
Tumour Type ◽  
Oncology Drug ◽  
To Receive ◽  
Drug Review

99 Background: New oncology drugs undergo detailed review of clinical, economic, and patient data. Thoroughly assessing these data can require lengthy review processes, in the absence of accelerated approval pathways. The aim of this study was to assess how cancer drug review times impact public funding recommendations. Methods: Drugs reviewed by Canada’s health technology assessment body, the pan-Canadian Oncology Drug Review (pCODR), from April 2012 to November 2020 were included in this study. Data was collected including Health Canada approval date, initial and final funding recommendations, treatment intent, drug class, clinical indication (tumour type) and incremental cost-effectiveness ratios (ICER). Univariable and multivariable analyses were used to determine the association between funding recommendations and review times. Results: Of the 227 applications submitted to pCODR, 168 had received positive funding recommendations. Amongst the total drug applications, 24 (14.3%) drugs were intended for the treatment of thoracic cancers, 19 (11.3%) for gastrointestinal cancers, 17 (10.1%) for genitourinary cancers, 17 (10.1%) for breast cancer, and 91 (54.2%) for other tumour sites. Median time from pCODR submission to final recommendation was longer for drugs indicated for the treatment of lung and breast cancer compared to those indicated for treatment of other tumours (223 vs. 212 vs. 203 days, respectively; Kruskal-Wallis p = 0.0322). Drugs with longer review times were more likely to receive a negative pCODR recommendation, even when adjusting for ICER (157 vs 298 days, Wilcoxon p-value = 0.0003). There was no association between positive or negative funding recommendation and tumour type. Conclusions: Oncology drugs with longer review times are less likely to receive recommendation for public funding in Canada. Addressing factors contributing to variance in review times and standardizing the review process can ensure equitable access to cancer drugs.

Examining the relationship between the clinical benefit of oncology drug indications and the time from pan-Canadian Oncology Drug Review (pCODR) recommendation to public reimbursement.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19360-e19360
Author(s):  
Sasha Thomson ◽  
Louis Everest ◽  
Noah Witzke ◽  
Seanthel Delos Santos ◽  
Matthew C. Cheung ◽  
...  
Keyword(s):  
Clinical Benefit ◽  
Multivariable Analysis ◽  
Cancer Drug ◽  
Cancer Type ◽  
Inclusion Criteria ◽  
Oncology Drug ◽  
The Mean ◽  
American Society ◽  
The Relationship ◽  
Drug Review

e19360 Background: We examined if publicly reimbursed oncology drug indications with evidence of high clinical benefit, as measured by the American Society of Clinical Oncology Value Framework v2 (ASCO-VF), and European Society for Medical Oncology Magnitude of Clinical Benefit Scale v1.1 (ESMO-MCBS), received reimbursement status faster than those with lower clinical benefit from the time of pCODR recommendation. Methods: Oncology drug indications that received pCODR recommendations between Jan 2012 and July 2018 were identified. Indications that did not receive provincial reimbursement, without notice of compliance, or received a negative pCODR recommendation were excluded. The relationship between clinical benefit, as measured by ASCO-VF and ESMO-MCBS, and the time to reimbursement was evaluated using Spearman correlation coefficient, univariable, and multivariable linear regression analyses. Results: Overall, 84 indications met inclusion criteria yielding 80 ASCO-VF and 66 ESMO-MCBS scores. The mean ASCO-VF and ESMO-MCBS scores were 38.8 (SD = 23.8) and 3.0 (SD = 1.1) respectively. Higher ASCO-VF and ESMO-MCBS scores had low correlation with shorter time to provincial funding, (rho = -0.15, 95%CI -0.24, -0.06) and (rho = -0.25, 95%CI -0.34, -0.16) respectively. Univariable analyses showed that manufacturer reported incremental cost effectiveness ratio (ICER) values, year of pCODR recommendation, province and cancer type were associated with time to public reimbursement (all p < 0.0001). After adjusting for potential confounders in the respective multivariable analysis, ASCO-VF (p = 0.29) and ESMO-MCBS (p = 0.15) scores were not significantly associated with time to public reimbursement. Year of pCODR recommendation remained associated with time to public reimbursement (p < 0.001). Earlier years (2012-2014) had a shorter time to reimbursement (mean = 10.4 months) than later years (2015-2018) (mean = 14.5 months). Other factors that were associated with time to reimbursement in multivariable analysis were province (p < 0.001) and cancer type (p < 0.001). Conclusions: Currently, oncology drug indication with evidence of high clinical benefit do not appear to be funded faster than those with low clinical benefit. This suggests the need to prioritize cancer drug indications based on clinical benefit in order to allow for timely public reimbursement of cancer drugs with higher clinical benefit to patients.

VP02 Real-World Evidence (RWE) And CADTH Pan-Canadian Oncology Drug Review

2018 ◽  
Vol 34 (S1) ◽  
pp. 159-160
Author(s):  
Dolly Han ◽  
Missale Tiruneh ◽  
Alexandra Chambers ◽  
Adam Haynes
Keyword(s):  
Cost Effectiveness ◽  
Data Collection ◽  
Real World ◽  
Clinical Benefit ◽  
Cancer Drug ◽  
Duration Of Treatment ◽  
Expert Review ◽  
Oncology Drug ◽  
Real World Evidence ◽  
Drug Review

Introduction:The pan-Canadian Oncology Drug Review (pCODR) program was established by Canada's provincial and territorial Ministries of Health (except Quebec) to assess cancer drug therapies and make recommendations to guide drug reimbursement decisions. The pCODR Expert Review Committee (pERC) makes reimbursement recommendations, providing a rationale for the recommendation and next steps for stakeholders. The objective of this analysis was to identify reviews and reasons pERC has requested real-world evidence (RWE) data collection.Methods:A retrospective analysis of pERC Final Recommendations (January 2012 – May 2017) was conducted. pERC Final Recommendations include drug information, reimbursement recommendation, rationale for recommendation following pERC's Deliberative Framework (clinical benefit, patient-based values, economic evaluation, and adoption feasibility), next steps for jurisdictions to consider to support their funding decisions, summary of deliberations, and evidence in brief. Reviews were included if there was a next step advising the collection of RWE to reduce uncertainty in the drug under review.Results:Out of eighty-four reviews, forty-one (forty-eight percent) included a next step to collect RWE to address a gap in the available evidence. Reasons for RWE data collection, in descending order of frequency, were to inform: sequencing of available therapies; magnitude of clinical benefit and cost-effectiveness or the true cost-effectiveness; duration of treatment and cost-effectiveness; defining the population or disease progression; quality of life; and dosage.Conclusions:In almost half of pERC's recommendation there is an indication that there is a gap in the existing evidence that could potentially be addressed through the collection of RWE. This reflects the rising number of new cancer drugs, limited evidence supporting submissions (for example non-comparative studies), and newer drugs such as immunotherapies which may not have a fixed treatment duration. Further research includes development of mechanisms for RWE data collection to help inform pERC recommendations and assist stakeholders with adoption feasibility of reviewed drugs.

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