Breast cancer is an increasingly urgent problem in low- and mid-level resource regions of the world. Despite knowing the optimal management strategy based on guidelines developed in wealthy countries, clinicians are forced to provide less-than-optimal care when diagnostic or treatment resources are lacking. For this reason, it is important to identify which resources most effectively fill health care needs in limited-resource regions, where patients commonly present with more advanced disease at diagnosis, and to provide guidance on how new resource allocations should be made to maximize improvement in outcome. Established in 2002, the Breast Health Global Initiative (BHGI) created an international health alliance to develop evidence-based guidelines for countries with limited resources to improve breast health outcomes. The BHGI serves as a program for international guideline development and as a hub for linkage among clinicians, governmental health agencies, and advocacy groups to translate guidelines into policy and practice. The BHGI collaborated with 12 national and international health organizations, cancer societies, and nongovernmental organizations to host 2 BHGI international summits. The evidence-based BHGI guidelines, developed at the 2002 Global Summit, were published in 2003 as a theoretical treatise on international breast health care. These guidelines were then updated and expanded at the 2005 Global Summit into a fully comprehensive and flexible framework to permit incremental improvements in health care delivery, based on outcomes, cost, cost-effectiveness, and use of health care services.
Benjamin O. Anderson and Robert W. Carlson
Rui Fu, Rinku Sutradhar, Qing Li, Timothy P. Hanna, Kelvin K.W. Chan, Jonathan C. Irish, Natalie Coburn, Julie Hallet, Anna Dare, Simron Singh, Ambica Parmar, Craig C. Earle, Lauren Lapointe-Shaw, Monika K. Krzyzanowska, Antonio Finelli, Alexander V. Louie, Nicole J. Look Hong, Ian J. Witterick, Alyson Mahar, David Gomez, Daniel I. McIsaac, Danny Enepekides, David R. Urbach, and Antoine Eskander
No population-based study exists to demonstrate the full-spectrum impact of COVID-19 on hindering incident cancer detection in a large cancer system. Building upon our previous publication in JNCCN, we conducted an updated analysis using 12 months of new data accrued in the pandemic era (extending the study period from September 26, 2020, to October 2, 2021) to demonstrate how multiple COVID-19 waves affected the weekly cancer incidence volume in Ontario, Canada, and if we have fully cleared the backlog at the end of each wave.
Jad Chahoud, Adele Semaan, and Alyssa Rieber
exacerbated by an unequal resource allocations and severe socioeconomic disparities across the country. 7 As described in the social ecological model, health outcomes depend on various factors at the personal (patient), organizational (provider), and system
Wendy R. Tate and Lee D. Cranmer
Background: Clinical study sites often do not achieve anticipated accrual to clinical trials, wasting critical patient, material, and human resources. The expensive and extensive process to bring a drug to approval highlights the need to streamline clinical pipeline processes. We sought to create a predictive accrual model to be used when considering clinical trial activation at the level of the individual site. Materials and Methods: This retrospective cohort study used 7 years of registry data from treatment and supportive care interventional studies at a single academic cancer center to build a negative binomial regression model with local and protocol variables known prestudy. Actual, team-predicted, and model-predicted accrual and sensitivity/specificity were calculated. Results: To build the model, 207 trials were used. Investigational drug application, disease team, number of national sites, local Institutional Review Board use, total national accrual time, accrual completed, and national enrollment goal were independently and significantly associated with accrual. Predicted accrual was 94% of actual, maintaining predictive value at multiple cutoff values. Validation included 61 trials. The model correctly predicted whether a study would accrue at least 4 subjects 75% of the time. Correlation at the category level was 44.3%, and model sensitivity and specificity are 70% and 78%, respectively. Conclusions: We identified and validated national and local key factors associated with accrual at our site. This methodology has not been previously validated broadly with the intent of trial feasibility. Model validation shows it to be an accurate and quick metric in anticipating accrual success that can be used for resource allocation.
Gaurav Kumar, Priyanka Chaudhary, Aiden Quinn, and Dejun Su
(institutional commitment, resource allocation, decentralization of IRB). Conclusion: Healthcare providers face complex, multifaceted barriers to clinical trial enrollment and participation, which exist at virtually every step of the clinical trial process. To
Kai-li Liang, Sean A. Tackett, Valerie Peterson, Tricia Patel, Michelle Turner, Sarah Sagorsky, Julie Brahmer, Christine Hann, Patrick Forde, Jarushka Naidoo, Kristen A. Marrone, David Ettinger, Ilene S. Browner, Vincent Lam, Russell K. Hales, Khinh R. Voong, and Josephine L. Feliciano
requiring treatment for irAE were associated with an increased risk of hospitalization. Understanding of risk factors for irAE hospitalization may provide utility for educating outpatient oncology providers and for resource allocation.
Youmna Ashraf Sherif, Sukriti Bansal, Rachel W. Davis, Marcia Barnett, Umang M. Parikh, Hunter Bechtold, Hudson Holmes, Ahmad N. Elhajj, Jed G. Nuchtern, Chad T. Wilson, and Cary Hsu
United States outlined recommendations on the performance of surgeries during this time to minimize viral transmission, prioritize resource allocation, and avoid peri-operative complications. These recommendations included the delay of non-urgent cases
Melissa A. Simon, Laura S. Tom, and XinQi Dong
in resource allocation at a community area level that can drive poor cancer outcomes. This picture might not be clear from reading the article. Every time we design, conduct, and publish a study, we need to be thoughtful about what the end goal
Emily A. Harlan and Andrew G. Shuman
accessible. 6 Although ethically sound consensus recommendations exist to guide some aspects of scarce resource allocation, the potential real-world outcomes of allocation strategies remain largely unknown. In this issue of JNCCN , Hantel et al 7
Daniel P. Kronish and Richard T. Penson
. Wonderfully, basic scientific endeavors have produced exciting new agents, and the real world of clinical science has to realign with the high call to service. Medicine has moved beyond using RCTs for scarce resource allocation. Now, beyond theory and 50