Evolving Economics: The Erosion of Medicare Reimbursement in Breast Surgery (2003-2023).

INTRODUCTION: Medicare significantly influences reimbursement rates, setting a standard that impacts private insurance policies. Despite declining rates in various specialties, the magnitude of these trends has not been examined in breast surgery. This study examines Medicare reimbursement trends for breast surgery operations. METHODS: Data for 10 breast operations from 2003 to 2023 were collected from the Medicare Physician Fee Look-Up Tool and yearly reimbursement was computed using the conversion factor. The year-to-year percentage change in reimbursement was calculated, and the overall median change was compared with the consumer price index (CPI) for inflation evaluation. All data were adjusted to 2023 United States dollars. The compound annual growth rate (CAGR) was calculated using inflation-adjusted data. RESULTS: Over the study period, reimbursement for the 10 breast operations had a mean unadjusted percentage increase of + 25.17%, while the CPI increased by 69.15% (p < 0.001). However, after adjustment, overall reimbursement decreased by - 20.70%. Only two operations (lumpectomy and simple mastectomy) saw increased inflation-adjusted Medicare reimbursement (+ 0.37% and + 3.58%, respectively). The CAGR was - 1.54% overall but remained positive for the same two operations (+ 0.02% and + 0.18%, respectively). Based on these findings, breast surgeons were estimated to be reimbursed $107,605,444 less in 2023 than if rates had kept pace with inflation over the past decade. CONCLUSION: Inflation-adjusted Medicare reimbursement rates for breast surgeries have declined from 2003 to 2023. This downward trend may strain resources, potentially leading to compromises in care quality. Surgeons, administrators, and policymakers must take proactive measures to address these issues and ensure the ongoing accessibility and quality of breast surgery.

Nodal Surgery for Patients ≥ 70 Undergoing Mastectomy for DCIS? Choose Wisely.

BACKGROUND: Routine sentinel lymphadenectomy (SLNB) for early-stage HR+/HER2- breast cancer in women ≥70 is discouraged by Choosing Wisely, but whether SLNB can be routinely omitted in women ≥70 with DCIS undergoing mastectomy is unclear. This study aims to evaluate rates of axillary surgery and nodal positivity (pN+) in this population to determine the impact of axillary surgery on treatment decisions. METHODS: Females ≥70 with DCIS undergoing mastectomy were identified from the National Cancer Database (2012-2020). The rate of upstaging to invasive cancer (≥pT1) or pN+ was assessed. Subset analyses were conducted for ER+ patients. Adjuvant therapies were evaluated among ≥pT1 patients after stratifying by nodal status. RESULTS: Of 9,030 patients, 1,896 (21%) upstaged to ≥pT1. Axillary surgery was performed in 86% of patients, predominantly sentinel lymphadenectomy (SLNB, 65%). Post hoc application of Choosing Wisely criteria demonstrated that 93% of the entire cohort and 97% of ER+ DCIS patients could have avoided axillary surgery. Nodal positivity was 0.3% among those who didn't upstage, and 12% among those upstaging to ≥pT1, with <2% having pN2-3 disease, irrespective of receptor subtype. Node-positive patients had higher adjuvant therapy usage, but there was no recommendation for adjuvant chemotherapy or radiation for 71% and 66% of pN+ patients, respectively. CONCLUSIONS: Axillary surgery can be omitted for most patients ≥70 undergoing mastectomy for ER+ DCIS, aligning with recommendations for invasive cancer, and omission can be considered in those with ER- disease. Future guidelines incorporating preoperative imaging, as in the SOUND trial, may aid in identifying patients benefiting from axillary surgery.

Should Palpable Nodes Be Exclusionary in Patients Who Are Otherwise Candidates for ACOSOG Z0011-Type Trials?

BACKGROUND: Palpable nodes were exclusionary in American College of Surgeons Oncology Group (ACOSOG) Z0011, while SINODAR-ONE excluded those with positive axillary nodes by palpation and ultrasound. To determine whether clinical nodal status should be exclusionary in those fulfilling pathologic criteria for ACOSOG Z0011 and similar trials, this study analyzed the accuracy and implications of clinical nodal positivity. METHODS: Patients ≥ 18 years old with cT1-T2, cN0-cN1, M0 breast cancer were identified in the National Cancer Database between 2004 and 2019. Subset characteristics of cN1 and cN0 were compared with respect to final pathologic nodal status and overall survival (OS). RESULTS: Of 57,823 patients identified, 77.0% were cT1 and 23.0% were cT2. Of the 93.9% of patients who were staged as cN0, 16.7% were pN1; of the remaining 6.1% staged as cN1, 9.6% were found to be pN0. Among cN1/pN0 patients, 14.9% underwent axillary dissection without sentinel node biopsy. There was no difference in adjusted OS for patients staged as cN0 versus cN1 who were found to be pN1 (HR 1.13, 95% CI 0.93-1.37, p = 0.22), a finding that persisted on subset analysis in those with two positive nodes (HR 0.91, 95% CI 0.62-1.33, p = 0.63). CONCLUSIONS: Clinical nodal stage does not affect OS in pN1 patients. Clinical nodal assessment can both overstage patients and result in unnecessary axillary surgery. These data suggest that cN1 patients who are otherwise candidates for a Z0011-like paradigm should still be considered eligible. Their final candidacy should be determined by surgical lymph node pathology and not preoperative clinical status.

What Proportion of BRCA-Associated Breast Cancer Is Human Epidermal Growth Factor 2-Low and Eligible for Additional Targeted Therapy?

INTRODUCTION: DESTINY B04 provided clinical meaning to a new classification of human epidermal growth factor 2 (HER2) expression in breast cancer: HER2-low. Patients with germline breast cancer type 1 gene pathogenic variants (gBRCA1) often develop triple negative breast cancer (TNBC), but the proportion who could be classified as HER2-low and qualify for an additional targeted therapy option is unknown. This study aims to characterize the proportion of gBRCA1 or germline breast cancer type 2 gene pathogenic variants patients for whom these novel targeted therapies may be an option. METHODS: We performed a retrospective chart review of patients with gBRCA1/2 treated at our institution for invasive breast cancer from 2000 to 2021. Synchronous or metachronous contralateral breast cancers were recorded separately. HER2 status was determined by immunohistochemistry and fluorescence in situ hybridization. We excluded patients without complete HER2 data. RESULTS: Among the 95 breast cancers identified in our cohort of 85 gBRCA1/2 patients, 41 (43%) were TNBC, 38 (40%) were hormone receptor positive (HR+)/HER2-negative, and 16 (17%) were HER2-positive based on standard conventions. We found that 82% of the HR+/HER2-cancers and 66% of TNBCs would be reclassified as HER2-low. After stratifying by BRCA gene status, 64% of cancers in patients with gBRCA1 and 58% of cancers in patients with germline breast cancer type 2 gene pathogenic variants were HER2-low. CONCLUSIONS: A significant portion of gBRCA1/2 patients who were previously diagnosed with TNBC or HR+/HER2- breast cancer would now be classified as HER2-low and could be considered for the use of trastuzumab deruxtecan in the metastatic setting. Outcome differences from therapy changes in this cohort should now be assessed.

Should patients with hormone receptor-positive, HER2-negative breast cancer and one or two positive sentinel nodes undergo axillary dissection to determine candidacy for adjuvant abemaciclib?

BACKGROUND: The monarchE trial demonstrated improved outcomes with the use of adjuvant abemaciclib in patients with high-risk hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer defined as ≥4 positive lymph nodes (+LNs) or one to three +LNs with one or more additional high-risk features (HRFs). The proportion of patients with one or two positive sentinel lymph nodes (+SLNs) without HRFs who had ≥4 +LNs at the time of completion axillary lymph node dissection (cALND), and who therefore qualified for receipt of abemaciclib, was investigated. METHODS: Females with pathologically node-positive nonmetastatic HR+/HER2- breast cancer stratified by the number of +SLNs and +LNs and the presence of one or more HRFs were identified from the National Cancer Database (2018-2019). The proportion of patients meeting the criteria for abemaciclib both before and after ALND was assessed. RESULTS: Of the 22,048 patients identified, 1578 patients underwent upfront surgery, had one or two +SLNs without HRFs, and went on to cALND. Only 213 (13%) of these patients had ≥4 +LNs; thus, cALND performed solely to determine abemaciclib candidacy would have constituted surgical overtreatment in 1365 patients (87%). When stratified by the number of +SLNs, only 10% of those with one +SLN and 24% of those with two +SLNs had ≥4 +LNs after cALND, which meets the criteria for abemaciclib. CONCLUSIONS: Patients with one +SLN without HRFs are unlikely to have ≥4 +LNs and should not be subjected to the morbidity of ALND in order to inform candidacy for abemaciclib. An individualized multidisciplinary discussion should be undertaken about the risk:benefit ratio of ALND and abemaciclib for those with two +SLNs.

"Cancer's a demon": a qualitative study of fear and multilevel factors contributing to cancer treatment delays.

PURPOSE: Delays initiating cancer therapy are increasingly common, impact outcomes, and have implications for health equity. However, it remains unclear (1) whether patients' beliefs regarding acceptable diagnostic to treatment intervals align with current guidelines, and (2) to what degree psychological factors contribute to longer intervals. We conducted a qualitative study with patients and cancer care team members ("providers"). METHODS: We interviewed patients with several common solid tumors as well as providers. Interviews were analyzed using an interpretive approach, guided by modified grounded theory. RESULTS: Twenty-two patients and 12 providers participated. Half of patients had breast cancer; 27% waited >60 days between diagnosis and treatment. Several themes emerged. (1) Patients felt treatment should begin immediately following diagnosis, while providers' opinion on the goal timeframe to start treatment varied. (2) Patients experienced psychological distress while waiting for treatment. (3) Participants identified logistical, social, and psychological sources of delay. Fear related to multiple aspects of cancer care was common. Emotion-driven barriers could manifest as not taking steps to move ahead, or as actions that delayed care. (4) Besides addressing logistical challenges, patients believed that education and anticipatory guidance, from their care team and from peers, may help overcome psychological barriers to treatment and facilitate the start of therapy. CONCLUSIONS: Patients feel an urgency to start cancer therapy, desiring time frames shorter than those included in guidelines. Psychological distress is frequently both a contributor to, and a consequence of, treatment delays. Addressing multilevel barriers, including psychological ones, may facilitate timely treatment and reduce distress.

Development of a Multilevel Model to Identify Patients at Risk for Delay in Starting Cancer Treatment.

Importance: Delays in starting cancer treatment disproportionately affect vulnerable populations and can influence patients' experience and outcomes. Machine learning algorithms incorporating electronic health record (EHR) data and neighborhood-level social determinants of health (SDOH) measures may identify at-risk patients. Objective: To develop and validate a machine learning model for estimating the probability of a treatment delay using multilevel data sources. Design, Setting, and Participants: This cohort study evaluated 4 different machine learning approaches for estimating the likelihood of a treatment delay greater than 60 days (group least absolute shrinkage and selection operator [LASSO], bayesian additive regression tree, gradient boosting, and random forest). Criteria for selecting between approaches were discrimination, calibration, and interpretability/simplicity. The multilevel data set included clinical, demographic, and neighborhood-level census data derived from the EHR, cancer registry, and American Community Survey. Patients with invasive breast, lung, colorectal, bladder, or kidney cancer diagnosed from 2013 to 2019 and treated at a comprehensive cancer center were included. Data analysis was performed from January 2022 to June 2023. Exposures: Variables included demographics, cancer characteristics, comorbidities, laboratory values, imaging orders, and neighborhood variables. Main Outcomes and Measures: The outcome estimated by machine learning models was likelihood of a delay greater than 60 days between cancer diagnosis and treatment initiation. The primary metric used to evaluate model performance was area under the receiver operating characteristic curve (AUC-ROC). Results: A total of 6409 patients were included (mean [SD] age, 62.8 [12.5] years; 4321 [67.4%] female; 2576 [40.2%] with breast cancer, 1738 [27.1%] with lung cancer, and 1059 [16.5%] with kidney cancer). A total of 1621 (25.3%) experienced a delay greater than 60 days. The selected group LASSO model had an AUC-ROC of 0.713 (95% CI, 0.679-0.745). Lower likelihood of delay was seen with diagnosis at the treating institution; first malignant neoplasm; Asian or Pacific Islander or White race; private insurance; and lacking comorbidities. Greater likelihood of delay was seen at the extremes of neighborhood deprivation. Model performance (AUC-ROC) was lower in Black patients, patients with race and ethnicity other than non-Hispanic White, and those living in the most disadvantaged neighborhoods. Though the model selected neighborhood SDOH variables as contributing variables, performance was similar when fit with and without these variables. Conclusions and Relevance: In this cohort study, a machine learning model incorporating EHR and SDOH data was able to estimate the likelihood of delays in starting cancer therapy. Future work should focus on additional ways to incorporate SDOH data to improve model performance, particularly in vulnerable populations.

The Impact of an Electromagnetic Seed Localization Device Versus Wire Localization on Breast-Conserving Surgery: A Matched-Pair Analysis.

BACKGROUND: For breast-conserving surgery (BCS), several alternatives to wire localization (WL) have been developed. The newest, electromagnetic seed localization (ESL), provides three-dimensional navigation using the electrosurgical tool. This study assessed operative times, specimen volumes, margin positivity, and re-excision rates for ESL and WL. METHODS: Patients who had ESL-guided breast-conserving surgery between August 2020 and August 2021 were reviewed and matched one-to-one with patients who had WL based on surgeon, procedure type, and pathology. Variables were compared between ESL and WL using Wilcoxon rank-sum and Fisher's exact tests. RESULTS: The study matched 97 patients who underwent excisional biopsy (n = 20) or partial mastectomy with (n = 53) or without (n = 24) sentinel lymph node biopsy (SLNB) using ESL. The median operative time for ESL versus WL for lumpectomy was 66 versus 69 min with SLNB (p = 0.76) and 40 versus 34.5 min without SLNB (p = 0.17). The median specimen volume was 36 cm3 using ESL versus 55 cm3 using WL (p = 0.001). For the patients with measurable tumor volume, excess tissue was greater using WL versus ESL (median, 73.2 vs. 52.5 cm3; p = 0.017). The margins were positive for 10 (10 %) of the 97 ESL patients and 18 (19 %) of the 97 WL patients (p = 0.17). In the ESL group, 6 (6 %) of the 97 patients had a subsequent re-excision compared with 13 (13 %) of the 97 WL patients (p = 0.15). CONCLUSIONS: Despite similar operative times, ESL is superior to WL, as evidenced by decreased specimen volume and excess tissue excised. Although the difference was not statistically significant, ESL resulted in fewer positive margins and re-excisions than WL. Further studies are needed to confirm that ESL is the most advantageous of the two methods.

Using Pointwise Mutual Information for Breast Cancer Health Disparities Research With SEER-Medicare Claims.

Identification of procedures using International Classification of Diseases or Healthcare Common Procedure Coding System codes is challenging when conducting medical claims research. We demonstrate how Pointwise Mutual Information can be used to find associated codes. We apply the method to an investigation of racial differences in breast cancer outcomes. We used Surveillance Epidemiology and End Results (SEER) data linked to Medicare claims. We identified treatment using two methods. First, we used previously published definitions. Second, we augmented definitions using codes empirically identified by the Pointwise Mutual Information statistic. Similar to previous findings, we found that presentation differences between Black and White women closed much of the estimated survival curve gap. However, we found that survival disparities were completely eliminated with the augmented treatment definitions. We were able to control for a wider range of treatment patterns that might affect survival differences between Black and White women with breast cancer.

Benefits versus drawbacks of delaying surgery due to additional consultations in older patients with breast cancer.

BACKGROUND: Additional evaluations, including second opinions, before breast cancer surgery may improve care, but may cause detrimental treatment delays that could allow disease progression. AIMS: We investigate the timing of surgical delays that are associated with survival benefits conferred by preoperative encounters versus the timing that are associated with potential harm. METHODS AND RESULTS: We investigated survival outcomes of SEER Medicare patients with stage 1-3 breast cancer using propensity score-based weighting. We examined interactions between the number of preoperative evaluation components and time from biopsy to definitive surgery. Components include new patient visits, unique surgeons, medical oncologists, or radiation oncologists consulted, established patient encounters, biopsies, and imaging studies. We identified 116 050 cases of whom 99% were female and had an average age of 75.0 (SD = 6.2). We found that new patient visits have a protective association with respect to breast cancer mortality if they occur quickly after diagnosis with breast cancer mortality subdistribution Hazard Ratios [sHRs] = 0.87 (95% Confidence Interval [CI] 0.76-1.00) for 2, 0.71 (CI 0.55-0.92) for 3, and 0.63 (CI 0.37-1.07) for 4+ visits at minimal delay. New patient visits predict worsened mortality compared with no visits if the surgical delay is greater than 33 days (CI 14-53) for 2, 33 days (CI 17-49) for 3, and 44 days (CI 12-75) for 4+. Medical oncologist visits predict worse outcomes if the surgical delay is greater than 29 days (CI 20-39) for 1 and 38 days (CI 12-65) for 2+ visits. Similarly, surgeon encounters switch from a positive to a negative association if the surgical delay exceeds 29 days (CI 17-41) for 1 visit, but the positive estimate persists over time for 3+ surgeon visits. CONCLUSION: Preoperative visits that cause substantial delays may be associated with increased mortality in older patients with breast cancer.

Clinicopathologic and sociodemographic factors associated with late relapse triple negative breast cancer in a multivariable logistic model: A multi-institution cohort study.

BACKGROUND: Most metastatic recurrences of triple negative breast cancer (TNBC) occur within five years of diagnosis, yet late relapses of TNBC (lrTNBC) do occur. Our objective was to develop a risk prediction model of lrTNBC using readily available clinicopathologic and sociodemographic features. METHODS: We included patients diagnosed with stage I-III TNBC between 1998 and 2012 at ten academic cancer centers. lrTNBC was defined as relapse or mortality greater than 5 years from diagnosis. Features associated with lrTNBC were included in a multivariable logistic model using backward elimination with a p < 0.10 criterion, with a final multivariable model applied to training (70%) and independent validation (30%) cohorts. RESULTS: A total 2210 TNBC patients with at least five years follow-up and no relapse before 5 years were included. In final multivariable model, lrTNBC was significantly associated with higher stage at diagnosis (adjusted Odds Ratio [aOR] for stage III vs I, 10.9; 95% Confidence Interval [CI], 7.5-15.9; p < 0.0001) and BMI (aOR for obese vs normal weight, 1.4; 95% CI, 1.0-1.8; p = 0.03). Final model performance was consistent between training (70%) and validation (30%) cohorts. CONCLUSIONS: A risk prediction model incorporating stage, BMI, and age at diagnosis offers potential utility for identification of patients at risk of development of lrTNBC and warrants further investigation.

A tool to predict disparities in the timeliness of surgical treatment for breast cancer patients in the USA.

PURPOSE: Breast cancer outcomes are impaired by both delays and disparities in treatment. This study was performed to assess their relationship and to provide a tool to predict patient socioeconomic factors associated with risk for delay. METHODS: The National Cancer Database was reviewed between 2004 and 2017 for patients with non-metastatic breast cancer managed with upfront surgery. Times to treatment were measured from the date of diagnosis. Patient, tumor, and treatment factors were assessed with attention paid to sociodemographic variables. RESULTS: 514,187 patients remained after exclusions, with 84.3% White, 10.8% Black, 3.7% Asian, and Hispanics comprising 5.6% of the cohort. Medicaid and uninsured patients had longer mean adjusted time to surgery (≥ 46 days) versus private (36.7 days), Medicare (35.9 days), or other governmental insurance (39.8 days). After adjustment, Black race and Hispanic ethnicity were most impactful, adding 6.0 and 6.4 preoperative days, 10.9 and 11.5 days to chemotherapy, 11.1 and 9.1 days to radiation, and 12.5 and 8.9 days to endocrine therapy, respectively. Income, education, and insurance, among other factors, also affected delay. A nomogram, including race and sociodemographic factors, was created to predict the risk of preoperative delay. CONCLUSION:  Significant disparities exist in timeliness of care for factors, including but not limited to, race and ethnicity. Although exact causes cannot be discerned, these data indicate population subsets whose intervals of care risk being longer than those specified by national quality standards. The nomogram created here may help direct resources to those at highest risk of incurring a treatment delay.