Overall, one-quarter (439, 26.8%) of women in our sample received mastectomy as initial surgical treatment. An additional 152 (9.3%) received mastectomy after one or more attempts at lumpectomy, but are counted for this analysis as initially receiving BCS. About one-third of the women who ultimately received mastectomy (222 of 591, 37.6%) had received reconstruction at the time of the survey.
shows patient characteristics and the distribution of receipt of initial mastectomy and receipt of reconstruction after mastectomy by subgroups. One-quarter had tumors <1 cm; 31.1% had tumors between 1 and 2 cm; and 39.7% had tumors greater than 2 cms. About one-fifth had DCIS. Patient report of clinical contraindications to BCS was uncommon. One-fifth of patients were less than 50, and 21.2% were 65 and older. About half of women were white, 26.6% were black, and 25.3% were Latina. One third of patients were high school graduates or less. Over half were partnered. About half were from Los Angeles, and 46.1% were from Detroit.
Patient characteristics and receipt of treatment
shows characteristics of the surgeon sample. One-fifth were female and the mean number of years in practice was 18.4 (SD,10.7); 61.7% were from Los Angeles and 38.3% were from Detroit. One-third devoted 15% or less of their practice to breast cancer and 16.8% devoted 50% or more. One-quarter indicated that their main practice affiliation was a cancer center, with 40.1% in a practice affiliated with an ACoS Cancer Program. One-third of surgeons scored low on the Multidisciplinary Communication scale (31.9%) and on the Availability of Clinical Information Scale. Two-thirds scored low on the Patient Decision Support scale. Only 14.9% of surgeons favored mastectomy in the treatment scenario.
Independent Correlates of Mastectomy
Receipt of initial mastectomy was positively associated with larger tumor size, advanced histologic grade, invasive disease behavior, and report of clinical contraindication to BCS (all p values<.001). No patient sociodemographic variables or surgeon characteristics, including practice organizational factors and surgeon attitudes toward treatment, were significantly associated with receipt of mastectomy after controlling for clinical factors. There were no interactions between SEER site and other covariates.
Between-Surgeon Variation in Receipt of Mastectomy
summarizes the multilevel model results for the mastectomy versus BCS outcome. Overall, the model explained 37% of the total variation in mastectomy rates with patient clinical factors and patient report of a clinical contraindication to BCS the primary explanatory variables (Column A). Seven percent of the variation in mastectomy versus BCS among women in our sample was attributed to individual surgeons after controlling for patients clinical and demographic factors (Column B). The proportion of variation unexplained at the surgeon level decreased to 4.0% when clinical contraindication to BCS was added to the model, indicating that including this variable reduced unexplained between-surgeon variation by 43% (column C). Surgeon variables added sequentially to the model did not further explain variance at the patient or surgeon level.
Random-effects model: Mastectomy versus Breast-conserving surgery1
Independent Correlates of Breast Reconstruction
Receipt of breast reconstruction after mastectomy was positively associated with smaller tumor size, non-invasive disease, younger age, and higher education. Reconstruction was positively associated with more multidisciplinary communication (adjusted odds ratio 3.7 and 3.4 for high and moderate levels of communication vs lowest level, Wald test 8.7, p=.012). On further evaluation we determined that this association was entirely due to one item in the scale: share of patients for whom the surgeon respondent consulted with a plastic surgeon prior to surgery. When one variable constructed from this item (1/3 or more vs. none or few patients referred to plastic surgeon prior to surgery) was included in a model substituting for the scale, the adjusted odds ratio was 6.6 (95 CI 3.2, 13.9).
We evaluated whether there were significant interactions between patient and surgeon level variables. There were no interactions between SEER site and other covariates. We then focused on patient education, because the base model showed that patients with lowest education were less likely to receive reconstruction (aOR .45, 95%CI .25, .78), and it seemed plausible that this effect of education might be modified by different surgeon communication styles or abilities. Patients with low education were widely dispersed across surgeon: 217 of 277 surgeons in the dataset had one or more low-education patients in their panel, and 62 had four patients or more. There was no evidence that the effect of education on reconstruction varied across surgeon (likelihood ratio chi sq 0.0, p>.9)
Between-Surgeon Variation in Receipt of Reconstruction
In contrast to the results for mastectomy, the individual surgeon explained a substantial amount of the patient variation in receipt of breast reconstruction (). Overall, the model explained 45% of the total patient variation with contributions from both patient and surgeon factors (Column A). Sixteen percent of variation in receipt of reconstruction among women who were treated with mastectomy was attributable to individual surgeons after controlling for patient clinical and demographic variables (Column B). Surgeon practice factors explained 31% of the between-surgeon variation (Column C). The effect of surgeon practice factors on between-surgeon variation in reconstruction was due solely to one item in the multidisciplinary communication scale: surgeon’s share of new patients in their practice for whom the surgeon talked to a plastic surgeon prior to surgery. When this item was entered in a model (binary variable few or no patients vs. more) with only patient level variables, it accounted for 31% of the between-surgeon variation in reconstruction. No other surgeon practice variables contributed to between-surgeon variation in reconstruction.
Random-effects model: Breast Reconstruction (yes vs no)1
The figure illustrates the surgeon effect directly on the scale of mastectomy and reconstruction rates. The figures show the estimated average surgeon rate of mastectomy and breast reconstruction for a typical patient in clinical practice across the different individual surgeons in the sample (indicated by the change in procedure rate moving from one end to the other of the surgeon distribution shown on the×axis). It also shows differences in procedure rates across important clusters of clinical characteristics described in the legend (shown by the difference in rates seen between curves on each graph). Thus, the magnitude of these absolute differences in use rates can be compared across surgeon and by key patient characteristics. For mastectomy, the graphs show that the magnitude of effect of having a clinical contraindication to breast conserving surgery dwarfs the differences in the propensity to do a mastectomy across surgeons. However, the effect, within an individual surgeon's practice, when comparing the mastectomy rates of a women with a smaller moderately differentiated tumor to one with a larger more poorly differentiated tumor, is similar in magintude to going from a surgeon with a low average rate of mastectomy to one with a high rate. For reconstruction, the differences in rate of reconstruction across surgeon (moving from left to right along the×axis) are for the most part larger than those within surgeon across clinical characteristics (moving across curves at any given x-axis location representing an individual surgeon).
Figure 1 The figures show the estimated rate of mastectomy and breast reconstruction for a typical patient in the dataset across the different individual surgeons. The base case represents a 50–64 year old, white high school graduate with moderately differentiated (more ...)
We performed a survey of patients recently diagnosed with breast cancer in the Los Angeles and Detroit metropolitan areas, and a companion survey of their attending surgeons to examine surgeon influences on variations in initial receipt of mastectomy and post-mastectomy reconstruction. We found that individual surgeon explained only a modest amount of the total variation in receipt of mastectomy (4%) after controlling for patient clinical and sociodemographic factors, but a much greater amount of total variation in reconstruction (16%). With regard to our first study question: more precise specification of receipt of treatment; better identification of women with contraindications to mastectomy; and inclusion of a more representative spectrum of breast cancer severity in our sample did not eliminate the surgeon level variation in rates of mastectomy and reconstruction that we had previously observed.9
Our second study question was whether practice organizational factors would explain some of the residual differences in mastectomy and reconstruction rates across surgeons. Our results suggest little association between mastectomy and these factors: Neither surgeon demographics (gender and years in practice), nor practice factors (breast cancer specialization and patient management process measures); nor attitudes about the treatment options measured using scenarios further explained between-surgeon variation in receipt of treatment. For reconstruction, one surgeon patient management process factor (share of the surgeons patients for whom the surgeon consulted with plastic surgeon prior to surgery) explained a substantial amount of the remaining between surgeon variation (31%).
Unique to the current analyses was the addition of surgeon patient management process factors to these models. These measures were developed based on the Chronic Care Model 8
which addresses basic elements for improving care in health systems including multidisciplinary care teams, and patient decision and care support.20,21
The model has been applied to research addressing the patterns of treatment and quality of care of patients with diabetes, heart disease, and depression. These types of factors have been highlighted by national organizations, including the IOM, as potential mechanisms for improving the quality of cancer care. Despite the interest in these management process factors, there have been no large studies that have incorporated these potentially important measures to evaluate patterns of treatment during the initial course of therapy. However, variables designed to measure most of the reasons that have been hypothesized as leading to practice variation (including surgeon experience, attitudes, and whether they practice in settings where there are opportunities for patient decision support and multidisciplinary input) did not further explain between-surgeon variation in treatment.
Strengths of the study included a large diverse sample of patients in two urban regions of the United States. We were able to link over 98% of respondent patients to an attending surgeon and nearly 75% of surgeons completed a survey. We collected a comprehensive set of surgeon level variables including demographics; level of specialization in breast cancer; and measures of surgeon patient management factors. However, our findings should be interpreted in the context of some limitations. The fact that our surveys were conducted in two large, urban geographic locations (Detroit and Los Angeles) limits the generalizability, particularly to more rural locations. We had limited power to detect small SES gradients in use of reconstruction because of the sample size and thus these results should be interpreted with some caution. Non-response and non-matching between some patients and surgeons may have also limited generalizability of our findings, particularly for surgeons with very low patient volumes. We were unable to account for the potential clustering of surgeons within practices or hospitals. However, the procedures we studied in this are commonly done by many general surgeons and one surgeon may practice at different hospital locations, lessening any potential impact of hospital-related clustering. We were also limited by the self-reported nature of some variables on both the patient and surgeon side.
Our findings have important implications for health policy. Lingering concerns about overtreatment with mastectomy at the hands of surgeons have diminished in response to recent research suggesting that surgeons’ recommendations for treatment are generally appropriate, and that patient preferences play an important role in decision-making.2,4
The very modest effect of individual surgeon on variation in mastectomy use observed in this study reinforces the notion that surgeons have largely adopted a uniform approach to the initial surgery options. Furthermore, between-surgeon variation in receipt of mastectomy was not attributable to surgeon demographics or patient management processes related to a more coordinated cancer care approach to treatment. While these practice management factors may be desirable for other reasons, they do not seem to explain differences in the surgical treatment options that women receive.
By contrast, the wide between-surgeon variation in receipt of breast reconstruction after mastectomy suggests that patients should be more cautious about how these decisions are made in clinical practice. In particular, the very strong effect of exposure to plastic surgeons prior to decisions about local therapy suggests that one possible result of multidisciplinary models of decision-making may be a much greater likelihood of receiving breast reconstruction after mastectomy. Prior literature suggests that patient satisfaction and quality of life related to breast reconstruction are high. But some patients who do not get it report lack of information or difficulties finding a surgeon who will perform it despite state laws that mandate insurance coverage.6,7
Our findings suggest that the treatment decision context and access to breast reconstruction vary across surgeon practices.
Our findings may inform interventions to reduce SES disparities in receipt of breast reconstruction after mastectomy. Similar to another study, we observed large socioeconomic disparities in the receipt of breast reconstruction after mastectomy. 6
A key question is whether the SES gradient in receipt of reconstruction varied across surgeon (reflecting a differential ability to bridge this disparity on the part of individual surgeons). We did not find any evidence of the heterogeneity of this effect. These findings suggest that interventions to reduce these disparities should be targeted broadly across the surgeon community.