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

Abstract 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.


| INTRODUCTION
Timeliness of breast cancer treatment is a concern. 1-3 The timing of definitive treatment is subject to many factors, including preoperative evaluation components which include consultations, imaging, and biopsies, 4 care transfers between institutions, 5 and multidisciplinary preoperative evaluations. 6,7 Preoperative consultations with a plastic surgeon to discuss immediate breast reconstruction may also cause delays.
Longer times between diagnosis and surgery for both invasive breast cancer 8 and ductal carcinoma in situ (DCIS) 9 are associated with detrimental survival and increased risk of disease progression. Relative overall mortality for patients having invasive breast cancer increases by 9% per month of delay, 8 while the risk of invasive disease progression for patients with DCIS increases by 13% per month of delay. 9 The delay-related relative increase in invasion and mortality is the end result of a potentially long growth interval that occurs before a tumor is diagnosed. 10 Clinical evaluation components (e.g., surgical or medical oncology consultations) in patients with breast cancer provide potential benefit by optimizing treatment. In addition, patients often seek second opinions, 11 and those opinions could be helpful. However, scheduling and attending extra evaluations and clinical consultations could delay time until surgery. This delay may allow disease progression and a consequent reduction in survival.
In this paper, we attempt to determine when a delay is worthwhile since the delay may allow for additional provider visits that confer a benefit. Related, we try to estimate the number of days after biopsy that extra consultations may no longer be helpful.

| METHODS
We used Surveillance Epidemiology and End Results (SEER) database linked to Medicare claims (https://seer.cancer.gov/registries/). As a population based registry, SEER-Medicare data is generalizable to the majority of individuals in the United States over 65 years old.
The SEER-Medicare database not only has detailed clinical and survival information, but also contains comprehensive claims data with dates regarding physician visits and procedures. This allowed us to investigate the relationship of survival outcomes with the number and type of visits in the interval between biopsy and surgery. We hypothesized that there would be interactions between the types of consultation in the preoperative interval and delays on outcomes. A limitation of SEER-Medicare is that the most recent cancer cases are not included since there is a time lag of several years before data is released. However, few other datasets have detailed information needed to explore this topic. We included surgically treated breast cancer cases that were diagnosed from 1992 to 2013 with followup through 2014. We included all individuals at least 66 years old with Medicare Parts A and B coverage for whom breast cancer was their first lifetime cancer. Those in Medicare Part C (i.e., managed care) were excluded. We excluded those who had neoadjuvant chemotherapy or radiotherapy.
We defined delay as months from first biopsy (in the month or prior month of diagnosis) to date of definitive surgical procedure after excluding those who had neoadjuvant chemotherapy, as described previously. 8,12 We defined a month as 30.44 days (365.25/12), and we examined intervals between biopsy and surgery of 1 to 180 days.
Our data indicated that effects changed at approximately one calendar month post biopsy. We examined the number of procedures and office visits on different days within the interval between the diagnostic biopsy and definitive procedure. We did not count multiple visits of the same type on the same day and did not include the end points (i.e., biopsy or surgical date) of the interval. We categorized procedures and grouped extreme numbers.
We used Medicare claims International Classification of Disease (ICD-9) and Healthcare Common Procedure Coding System (HCPCS) codes to determine type of visit (e.g., established or new patient visit) or procedure. We determined physician specialty using health care financing administration specialty codes. We evaluated the number of unique physicians by applying the NCI crosswalk to link physician identifiers over time. All codes are specified in the supporting information.
We investigated SEER-captured breast cancer-specific mortality using Fine and Gray regressions, 13 and overall survival using Cox regressions. We controlled for baseline differences among encounter groups using propensity score based weighting. 14 We estimated propensity scores separately for each component. We included the following variables in the propensity score model: age at diagnosis, Charlson comorbidity index, 15 Elixhauser score, 16 race, sex, SEER region of the country, marital status, metropolitan area size, tumor size, diagnosis year, whether nodes were examined, number of positive nodes, histology, tumor grade, ER/PR positivity, HER-2 positivity, tumor sequence, and AJCC stage. Therapeutic variables included mastectomy versus lumpectomy, reconstruction, adjuvant chemotherapy, and adjuvant radiation therapy. Patient ZIP code-level variables included the percent of the population with less than a high school education or living below the poverty line. We used restricted cubic splines 17 for continuous variables and robust standard errors. 14 In propensity-score base weighted regressions, we included main effects for procedure group (categorical variable) and treatment delay (continuous variable) and their interactions. We set the reference (subdistribution hazard ratio [sHR] = 1 or log sHR = 0) to be the survival effect under 0 relevant encounters and no treatment delay. We present cumulative incidence and survival curves by combining baseline functions with regression parameter estimates. For ease of presentation, we plotted four curves assuming zero or the maximum number of encounters, and delay of 0.5 or 3 months. We used STATA and a nominal p < .05 defined statistical significance.    The second column of Table 3 provides counts of the number of T A B L E 2 Characteristics of the type of encounters between biopsy and definitive surgery.  Note: Delay is defined as the interval between biopsy to definitive surgical treatment. The components count the number of days having the encounter or procedure of interest. We did not double count visits of the same type on the same day. encounters or procedures, which adds additional information to Table 2. The counts in Table 3 demonstrate that the absolute number of cases with multiple encounters of all types was large, even if the proportion was low. In supplemental Tables 1-12, we show descrip-tive statistics by selected procedure groupings before and after adjustment by propensity score based weighting.

| RESULTS
In Table 3, the effect of a one-month delay is associated with increased mortality of sHR =   Figure 2B depicts estimated breast cancer specific cumulative incidence curves. As we measured delay on a continuous scale, we present representative adjusted cumulative incidence curves when the delay time is set to 0.5 or 3 months, or the number of encounters is set to 0 or the maximum category.
Physician specialty makes a difference in the relationship of clinical encounters with delay-associated outcomes (Table 3 and Figure 2C,D). Visiting multiple radiation oncologists does not have an impact (Table 3 and Figure 2G,H).
In Table 3

| DISCUSSION
Preoperative disease evaluation is beneficial for optimizing treatment, but too many preoperative visits can be associated with treatment delays that affect survival outcomes. 8 This study attempts to delineate the extent to which delay reduces, and even reverses, the benefit of clinical evaluations before surgery. We found associations that may signify a trade-off in delaying breast cancer treatment. Having multiple physicians evaluate patients in a short time seems to be associated with better outcomes. As the delay increases with multiple evaluations, the association of those evaluations with survival turns negative.
Second opinions may be one reason why many cases have numerous unique physician encounters. Morrow et al. found that 19.1% of surveyed women with breast cancer had a second opinion, 18 and a recent study noted a 36% increase in transfers of care for breast cancer patients to another provider between 2004 and 2015. 5 Having a higher education and having genetic variants of uncertain significance has been associated with seeking second opinions. 19 While some studies have examined the reasons that patients seek second opinions and the resulting treatment decisions, 20 there do not seem to be many studies examining second opinions' effect on survival.
F I G U R E 2 Legend on next page.
Imaging for staging and identification of metastatic disease may also contribute to treatment delays. 21 With greater survival and number of approved treatments for metastatic disease, it may not be surprising that imaging for breast cancer has increased over time. 22 We did not find associations indicative of a survival impact of having repeated images or biopsies in the pre-surgery interval.
While the benefit of additional evaluations and imaging encounters on survival is unclear, there is increasing evidence that treatment delays are associated with worse outcomes. A number of large studies have found that treatment delays are associated with worsened mortality. 3,8,23 The effect of delay on outcomes may be causally related to tumor doubling times and rates of metastatic develpoment. 12  F I G U R E 2 (A) Log subdistribution hazard ratios (sHRs) showing the effect of delay (as defined as time from biopsy to surgery) on breast cancer mortality by the number of new patient visits. Note that the reference category is the group having 0 new patient visits in the interval between biopsy and surgery (sHR = 1, log sHR = 0). The median is shown by j and extreme values beyond which <12 cases have delays are represented by parentheses. In the short term, increasing number of encounters is associated with better survival, but the estimates stop becoming protective relative to no delay and no extra encounters once the lines cross zero. (B) Representative cumulative incidence curves using estimates from the propensity score weighted competing risk regression for four groups defined by when the delay equals 0.5 or 3 months, and the number of new patient visits equals 0 or 4+. The curves demonstrate that for patients having no new patient encounters, there is minimal difference in the time between diagnosis and surgery, while those having 4 or more encounters note a large disparity in mortality when delay increases. This suggests that the impact of delay is incrementally more significant in those visiting more providers for the first time (i.e., having more new patient encounters).

| CONCLUSION
While treatment delays are generally associated with worse outcomes, we found that some postponement of surgery related to patient encounters with health care providers could be beneficial.
For example, new patient visits, and particularly new medical oncology or surgery encounters, were associated with better survival outcomes if the encounters occurred within the first month after diagnosis. However, when accompanied by longer times to surgery, new patient visits were associated with worsened breast cancer mortality. Future research is needed to better understand the underlying reasons for these findings. For example, more detailed examination of those who have new patient encounters within the first month of diagnosis can identify care patterns that might be providing benefits to patients. Researchers could also examine possible mechanisms, such as disease progression, that might explain why encounters that occur with surgical delays of greater than 1 month are associated with worse mortality. Such future research will help clinicians assess when additional preoperative evaluations might be helpful, and when they might be harmful for patients.