The BRA Score was developed for use by reconstructive surgeons and their patients. It has potential utility in both surgical planning and informed consent. Seeing quantifiable risk estimates for different complications across various modalities can help the surgeon weigh them against the advantages of each modality. Similarly, walking a patient through this information can increase her involvement in and understanding of the surgical planning process . However, the BRA Score should not be used to determine surgical candidacy for any patient. It yields only one side of a two-sided equation and cannot replace the clinical judgment of the reconstructive surgeon. Similarly, it cannot be the sole basis of the informed consent process, but helps facilitate it with accessible and consolidated risk information. It is important to note the limitations of data from which the BRA Score is derived, as well as the absence to date of a study examining the tool’s external validity.

It is easiest to discuss the use and utility of the BRA Score with actual case-based examples. The examples that follow are two hypothetical patients undergoing mastectomy with immediate breast reconstruction. Let’s look at these patients and use the BRA Score to quantify the difference in risk for these two women. For demonstration purposes, one case example will be assessed using the BRA Score website, while the second will be assessed using the BRA Score App.

Patient A is a 30-year-old woman who has chosen to undergo a prophylactic risk-reducing double mastectomy for her recently diagnosed BRCA carrier status. She is 5′6″ tall and weighs 120 lbs. She does not smoke and has no comorbidities. This is the type of patient that is seen more and more often in clinical practice as we witness continuing improvements and the publicity in both genetic testing for and prophylactic treatment of high-risk mutations [32] www.​BRAScore.​org.

We start at the landing page in Fig. 11.4, which outlines some of the uses and limitations discussed above. We acknowledge understanding and click “Proceed.”

The homepage in Fig. 11.5 presents us with the characteristics that are taken into account in the BRA Score statistical models . There are demographics, comorbidities, and treatment details to fill in. Once these are complete with the details for “Patient A,” we can click the “Calculate Risk” button that appears, as in Fig. 11.6.

We see a risk profile that pops up for Patient A, shown in Fig. 11.7. In interpreting this, there are a few things to note, independent of the actual results. One is the superscript on various categories. These tell us which cohort the data is derived from. For example, the latest work with the Mastectomy Reconstruction Outcomes Consortium (MROC ) [29] yielded sufficient statistical power only for an analysis of “overall” complications, but had more single stage cases than prior studies, allowing for inclusion of those patients. Thus, the single-stage modality, the newest addition to the BRA Score, has a result for only “overall” complications. Similarly, the studies from which each data point is estimated vary in the exact definitions of the input and their weighting in the regressions. For example, those with granular familiarity with the ACS-NSQIP database know that it lacks thorough radiotherapy information [33]. Thus, the information that we input regarding radiotherapy is not factored into estimates based on NSQIP data, but is used for those derived from MROC data.

We can see from the probabilistic estimates in Fig. 11.7 that Patient A is a fairly low-risk patient across the board, as expected. Though we can intuit that she has a “low” risk of complications relative to published means, it is beneficial to have numerical estimates, particularly in this increasingly common patient with little outcomes data available because of the rarity of her situation prior to the era of testing and prophylactic double mastectomy .

Patient B is a 65 year-old woman undergoing unilateral mastectomy for a newly-diagnosed invasive ductal carcinoma and wants to minimize added procedures including those to the contralateral breast. She is 5′6″ tall and weighs 170 lbs. She smokes, but has agreed to quit 30 days prior to the procedure. She also has diabetes and hypertension. She has been deemed American Society of Anesthesiologists (ASA) class II due to the burden of her comorbidities.

The app is freely available in the Google Play and Apple Apps store for Android, respectively. We download and open the app to arrive at the screen depicted in Fig. 11.8. Information within the “Instructions,” “About Us,” and “Disclaimer” options are largely covered above, so we will proceed to press “Start.”

The app walks us through several questions, capturing the same information that is captured by the online interface in Fig. 11.9. After answering the last question and pressing “Next,” a review screen is offered to ensure that all questions were answered correctly and giving us the opportunity to change answers as appropriate, as shown in Fig. 11.10. When all characteristics are correctly entered, pressing “Results” takes us to the output.

The BRA Score app output for Patient B is depicted in Fig. 11.11. As expected, we see significantly higher risks across all categories than we did for Patient A. The default modality displayed on the results screen in the app is staged expander-implant reconstruction. However, we can also view predicted risks for autologous reconstructions. When selecting “Latissimus Flap,” for example, the results array changes to reflect the predicted probabilities for the relevant surgical technique, as shown in Fig. 11.12. Again, more specific numerical estimates of risk in this context allow for better cross-technique comparisons and expectation management. One notable limitation to the former use in this context is the fact that the data from which the risk models were derived code using Current Procedural Terminology (CPT) codes, which preclude differentiation between microvascular techniques.