Examining a decade of racial disparity in partial mastectomy and oncoplastic surgery

Jonczyk, Michael; Homsy, Christopher; Naber, Stephen P.; Chatterjee, Abhishek

doi:10.1002/jso.27173

Cited by 8 publications

(6 citation statements)

References 47 publications

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“…We also include the absolute disparity in YLLs between racial groups and the indices of disparity in mortality and YLLs based on race/ethnicity ( 68 ). These indices are modified coefficients of variation and are commonly used to study disparities in disease outcomes ( 69 , 70 ).…”

Section: The Mathematical Modelmentioning

confidence: 99%

Retrospective analysis of equity-based optimization for COVID-19 vaccine allocation

Stafford,

Dimitrov,

Ceballos

et al. 2023

PNAS Nexus

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Marginalized racial and ethnic groups in the United States were disproportionally affected by the COVID-19 pandemic. To study these disparities, we construct an age-and-race-stratified mathematical model of SARS-CoV-2 transmission fitted to age-and-race-stratified data from 2020 in Oregon and analyze counterfactual vaccination strategies in early 2021. We consider two racial groups: non-Hispanic White persons and persons belonging to BIPOC groups (including non-Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American-Indian or Alaska-Native persons, and Hispanic or Latino persons). We allocate a limited amount of vaccine to minimize overall disease burden (deaths or years of life lost), inequity in disease outcomes between racial groups (measured with five different metrics), or both. We find that, when allocating small amounts of vaccine (10% coverage), there is a trade-off between minimizing disease burden and minimizing inequity. Older age groups, who are at a greater risk of severe disease and death, are prioritized when minimizing measures of disease burden, and younger BIPOC groups, who face the most inequities, are prioritized when minimizing measures of inequity. The allocation strategies that minimize combinations of measures can produce middle-ground solutions that similarly improve both disease burden and inequity, but the trade-off can only be mitigated by increasing the vaccine supply. With enough resources to vaccinate 20% of the population the trade-off lessens, and with 30% coverage, we can optimize both equity and mortality. Our goal is to provide a race-conscious framework to quantify and minimize inequity that can be used for future pandemics and other public health interventions.

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Section: The Mathematical Modelmentioning

confidence: 99%

Retrospective analysis of equity-based optimization for COVID-19 vaccine allocation

Stafford,

Dimitrov,

Ceballos

et al. 2023

PNAS Nexus

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“…OPS is a safe and accepted option for breast cancer surgery 15,16 . As such, efforts should be made to improve accessibility to oncoplastic techniques in the management of breast cancer patients in the United States 17 . As societies begin to investigate training surgeons in OPS, learning curve studies such as ours demonstrating results are important in guiding teaching programs.…”

Section: Discussionmentioning

confidence: 99%

The adoption of oncoplastic surgery: Is there a learning curve?

Karamchandani

Jonczyk

Cruz-Ku

et al. 2023

Journal of Surgical Oncology

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Introduction: Oncoplastic surgery (OPS) is a form of breast conservation surgery involving partial mastectomy followed by volume displacement or replacement surgery. As the field of OPS is growing, we sought to determine if there was a learning curve to this surgery.Methods: A retrospective chart review was conducted of all patients who underwent OPS over a 6-year period with a single surgeon formally trained in both Plastic Surgery and Breast Oncology. Cumulative summation analysis (CUSUM) was performed on mean operative time to generate the learning curve and learning curve phases. Outcomes were compared between phases to determine significance.Results: Mean operative time decreased significantly across the 6-year period, generating three distinct learning curve phases: Learner phase (cases 1−23), Competence phase (24−73), and Mastery phase (74 and greater). The overall positive margin rate was 10.9% and there was no significant difference in rates between phases (p = 0.49). Overall complication rates, reoperation rates, and locoregional recurrence remained the same across all phases (p = 0.16; p = 0.65; p = 0.41). The rate of partial nipple loss decreased between phases (p = 0.02). Conclusion:As with many complex operations, there does appear to be a learning curve with OPS, as the operative time and the rates of partial nipple loss decreased over time.

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“…We also include indices of disparity in mortality and YLLs based on race/ethnicity [66]. These indices are modified coefficients of variation and are commonly used to study disparities in disease outcomes [67], [68]. For our optimization routine, we develop a coarse global search algorithm to find the vaccination strategy that minimizes a given objective function with a fixed amount of resources (vaccine doses) over a time frame of four months.…”

Section: The Optimization Problemmentioning

confidence: 99%

Retrospective Analysis of Equity-Based Optimization for COVID-19 Vaccine Allocation

Stafford¹,

Dimitrov

Ceballos

et al. 2023

Preprint

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Marginalized racial and ethnic groups in the United States were disproportionally affected by the COVID-19 pandemic. To study these disparities, we construct an age-and-race-stratified mathematical model of SARS-CoV-2 transmission fitted to age-and-race-stratified data from 2020 in Oregon and analyze counterfactual vaccination strategies in early 2021. We consider two racial groups: non-Hispanic White persons and persons belonging to BIPOC groups (including non-Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American Indian or Alaska Native persons, and Hispanic or Latino persons). We allocate a limited amount of vaccine to minimize overall disease burden (deaths or years of life lost), inequity in disease outcomes between racial groups (measured with five different metrics), or both. We find that, when allocating small amounts of vaccine (10% coverage), there is a trade-off between minimizing disease burden and minimizing inequity. Older age groups, who are at a greater risk of severe disease and death, are prioritized when minimizing measures of disease burden, and younger BIPOC groups, who face the most inequities, are prioritized when minimizing measures of inequity. The allocation strategies that minimize combinations of measures can produce middle-ground solutions that similarly improve both disease burden and inequity, but the trade-off can only be mitigated by increasing the vaccine supply. With enough resources to vaccinate 20% of the population the trade-off lessens, and with 30% coverage, we can optimize both equity and mortality. Our goal is to provide a race-conscious framework to quantify and minimize inequity that can be used for future pandemics and other public health interventions.

show abstract

Examining a decade of racial disparity in partial mastectomy and oncoplastic surgery

Cited by 8 publications

References 47 publications

Retrospective analysis of equity-based optimization for COVID-19 vaccine allocation

Retrospective analysis of equity-based optimization for COVID-19 vaccine allocation

The adoption of oncoplastic surgery: Is there a learning curve?

Retrospective Analysis of Equity-Based Optimization for COVID-19 Vaccine Allocation

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