Non-clinical Drivers of Variation in Preoperative MRI Utilization for Breast Cancer

Screening and diagnostic breast MRI: how do they impact surgical treatment? Insights from the MIPA study

OBJECTIVES

To report mastectomy and reoperation rates in women who had breast MRI for screening (S-MRI subgroup) or diagnostic (D-MRI subgroup) purposes, using multivariable analysis for investigating the role of MRI referral/nonreferral and other covariates in driving surgical outcomes.

METHODS

The MIPA observational study enrolled women aged 18-80 years with newly diagnosed breast cancer destined to have surgery as the primary treatment, in 27 centres worldwide. Mastectomy and reoperation rates were compared using non-parametric tests and multivariable analysis.

RESULTS

A total of 5828 patients entered analysis, 2763 (47.4%) did not undergo MRI (noMRI subgroup) and 3065 underwent MRI (52.6%); of the latter, 2441/3065 (79.7%) underwent MRI with preoperative intent (P-MRI subgroup), 510/3065 (16.6%) D-MRI, and 114/3065 S-MRI (3.7%). The reoperation rate was 10.5% for S-MRI, 8.2% for D-MRI, and 8.5% for P-MRI, while it was 11.7% for noMRI (p ≤ 0.023 for comparisons with D-MRI and P-MRI). The overall mastectomy rate (first-line mastectomy plus conversions from conserving surgery to mastectomy) was 39.5% for S-MRI, 36.2% for P-MRI, 24.1% for D-MRI, and 18.0% for noMRI. At multivariable analysis, using noMRI as reference, the odds ratios for overall mastectomy were 2.4 (p < 0.001) for S-MRI, 1.0 (p = 0.957) for D-MRI, and 1.9 (p < 0.001) for P-MRI.

CONCLUSIONS

Patients from the D-MRI subgroup had the lowest overall mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). This analysis offers an insight into how the initial indication for MRI affects the subsequent surgical treatment of breast cancer.

KEY POINTS

• Of 3065 breast MRI examinations, 79.7% were performed with preoperative intent (P-MRI), 16.6% were diagnostic (D-MRI), and 3.7% were screening (S-MRI) examinations. • The D-MRI subgroup had the lowest mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). • The S-MRI subgroup had the highest mastectomy rate (39.5%) which aligns with higher-than-average risk in this subgroup, with a reoperation rate (10.5%) not significantly different to that of all other subgroups.

Current Trends in the Utilization of Preoperative Breast Magnetic Resonance Imaging Among Women With Newly Diagnosed Breast Cancer

PURPOSE

The clinical benefit of preoperative breast magnetic resonance imaging (MRI) for early-stage breast cancer (BC) remains controversial. We examined trends and the associated factors of preoperative breast MRI use.

METHODS

This study cohort, constructed from Optum Clinformatics database, included women with early-stage BC who had a cancer surgery between March 1, 2008, and December 31, 2020. Preoperative breast MRI was performed between the date of BC diagnosis and index surgery. Multivariable logistic regressions, one for elderly (65 years and older) and the other for non-elderly patients (younger than 65 years), were performed to examine factors associated with the use of preoperative MRI.

RESULTS

Among 92,077 women with early-stage BC, the crude rate of preoperative breast MRI increased from 48% in 2008 to 60% in 2020 for nonelderly and from 27% to 34% for elderly women. For both age groups, non-Hispanic Blacks were less likely (odds ratio [OR]; 95% CI, younger than 65 years: 0.75, 0.70 to 0.81; 65 years and older: 0.77, 0.72 to 0.83) to receive preoperative MRI than non-Hispanic White patients. Across Census divisions, the highest adjusted rate was observed in Mountain division (OR compared with New England; 95% CI, younger than 65 years: 1.45, 1.27 to 1.65; 65 years and older: 2.42, 2.16 to 2.72). Other factors included younger age, fewer comorbidities, family history of BC, axillary node involvement, and neoadjuvant chemotherapy for both age groups.

CONCLUSION

The use of preoperative breast MRI has steadily increased. Aside from clinical factors, age, race/ethnicity, and geographic location were associated with preoperative MRI use. This information is important for future implementation or deimplementation strategies of preoperative MRI.

Perioperative magnetic resonance imaging in breast cancer care: Distinct adoption trajectories among physician patient-sharing networks

BACKGROUND

Despite no proven benefit in clinical outcomes, perioperative magnetic resonance imaging (MRI) was rapidly adopted into breast cancer care in the 2000's, offering a prime opportunity for assessing factors influencing overutilization of unproven technology.

OBJECTIVES

To examine variation among physician patient-sharing networks in their trajectory of adopting perioperative MRI for breast cancer surgery and compare the characteristics of patients, providers, and mastectomy use in physician networks that had different adoption trajectories.

METHODS AND FINDINGS

Using the Surveillance, Epidemiology, and End Results-Medicare database in 2004-2009, we identified 147 physician patient-sharing networks (caring for 26,886 patients with stage I-III breast cancer). After adjusting for patient clinical risk factors, we calculated risk-adjusted rate of perioperative MRI use for each physician network in 2004-2005, 2006-2007, and 2008-2009, respectively. Based on the risk-adjusted rate, we identified three distinct trajectories of adopting perioperative MRI among physician networks: 1) low adoption (risk-adjusted rate of perioperative MRI increased from 2.8% in 2004-2005 to 14.8% in 2008-2009), 2) medium adoption (8.8% to 45.1%), and 3) high adoption (33.0% to 71.7%). Physician networks in the higher adoption trajectory tended to have a larger proportion of cancer specialists, more patients with high income, and fewer patients who were Black. After adjusting for patients' clinical risk factors, the proportion of patients undergoing mastectomy decreased from 41.1% in 2004-2005 to 38.5% in 2008-2009 among those in physician networks with low MRI adoption, but increased from 27.0% to 31.4% among those in physician networks with high MRI adoption (p = 0.03 for the interaction term between trajectory group and time).

CONCLUSIONS

Physician patient-sharing networks varied in their trajectory of adopting perioperative MRI. These distinct trajectories were associated with the composition of patients and providers in the networks, and had important implications for patterns of mastectomy use.