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The American Journal of Surgery
journal homepage: www.americanjournalofsurgery.com
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The American Journal of Surgery”
PLATINO
Original Research Article
Survival impact of treatment utilization and margin status after resection of adrenocortical carcinoma
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Kelvin Memeha, Sara Abou Azar b, Oluwasegun Afolaranmi ℃, Tanaz M. Vaghaiwalla d,*
a Department of Surgery, Methodist University Hospital, Memphis, TN, USA
b Division of Endocrine Surgery, Department of Surgery, University of Chicago Medicine, Chicago, IL, USA
“ Cancer Research UK Cambridge Institute University of Cambridge, GB, United Kingdom
d Division of Endocrine Surgery, DeWitt Daughtry Family Department of Surgery, University of Miami, Miami, FL, USA
ABSTRACT
Background: This study examines the combined impact of margin status and adjuvant therapy utilization on overall survival (OS) for adrenocortical carcinoma (ACC) patients undergoing surgery with curative intent.
Methods: The 2004-2020 National Cancer Database (NCDB) was queried for ACC patients >18yrs undergoing curative surgery (no debulking), subdivided into RO and R1/R2-groups, and analyzed using inverse-probability-weighted Cox Proportional Hazard-model.
Results: Of 5023 ACC patients, 3193 underwent curative surgery, 2213 (69 %) had R0 margins. Compared to the R0, the R1/R2 group had a decreased OS by 15.6 months (HR = 1.89, p = 0.002). While there has been no significant improvement in margin status over the years studied (2008-2017), there has been an overall increase in the proportion of patients receiving adjuvant therapy regardless of margin status, and the adverse impact of a positive margin on survival has decreased [HR 2.20 vs 1.76]
Conclusions: R1/R2 margins are associated with decreased OS. The adverse impact of R1/R2 margins on OS decreased over time while adjuvant therapy utilization increased for all patients.
1. Introduction
Adrenocortical carcinoma (ACC) is a rare and aggressive malignancy of the adrenal cortex, with an incidence rate of 1.02 per million in the United States.14 The combination of aggressive tumor biology and advanced-stage presentation confers ACC patients with a poor prognosis - with a 5-year overall survival (OS) of 50 %.5-7 The management of ACC has evolved over the last two decades. The FIRM-ACT trial by Fassnacht et al.8 demonstrated some promise in combination systemic therapy for advanced ACC; however, the overall survival rates have not changed dramatically, underscoring the need for more effective treatment. Sur- gical resection, with or without an en-bloc resection of adjacent struc- tures to achieve an R0 margin, remains the cornerstone of curative treatment for ACC.8-11 ACC patients who undergo surgical resection have a significantly improved median OS compared to those who do not un- dergo surgery.12-14 While achieving an RO resection is critical for improving survival,13,14 studies have shown that 14-30.6 % of ACC pa- tients have a positive margin after surgery.5,9
Anderson Jr et al., examined 1553 ACC patients who had a surgical resection, using the National Cancer Database (NCDB) from 1998 to 2012, and found that patients with micro- and macroscopically positive
margins have significantly worse survival outcomes compared to those with negative margins - emphasizing the pivotal role of surgical margin status.5 Estimated median and 5-year overall survival for ACC patients undergoing RO resection were 96.3 months and 64.8 % compared to 25.1 months and 33.8 % for patients undergoing an R1 resection.º In addition to margin positivity, previous research has highlighted certain other factors associated with poor prognosis in ACC, including intraoperative tumor capsule violation or spillage, extra-adrenal extension, lymph node involvement, and Ki-67 proliferation index >10 %.10,15,16
The utilization of adjuvant therapies, such as radiation and chemo- therapy, has become prevalent in recent years.2 These therapies aim to improve the survival outcomes of patients with adverse features, such as positive surgical margins. While studies suggest improved survival with the addition of adjuvant therapies after surgical resection,1,2,5,17,18 there is limited understanding of the trends and pattern of utilization of these therapies when considering margin status and whether their impact has evolved. The aim of this study is as follows: evaluate the current survival trends for ACC patients who underwent surgery with curative intent, explore the practice pattern and trends in adjuvant therapy utilization as it relates to margin status, and examine the differential and combined impact of surgical margin status and utilization of adjuvant therapy on survival.
* Corresponding author.
E-mail address: tmv12@med.miami.edu (T.M. Vaghaiwalla).
https://doi.org/10.1016/j.amjsurg.2024.115999
2. Methods
2.1. Patient selection & study design
This study utilized the 2004 to 2020 National Cancer Database (NCDB) registry, which comprises de-identified data from over 1500 hospital cancer registries nationwide. The NCDB is a joint project of the Commission on Cancer at the American College of Surgeons and the American Cancer Society. For this study, we queried the NCDB registry for all adult patients (≥18 years of age) diagnosed with adrenocortical carcinoma, identified using the International Classification of Disease for Oncology third edition (ICD-O-3) site codes C740, C741, C749, and his- tology code 8370/3.
The variable of interest was surgical margin status. To this end, pa- tients were divided into two groups based on their surgical resection margin: the R0 group (negative surgical margin and no gross disease left) and the R1/R2 group (microscopic or grossly positive surgical margin). This study included only patients who underwent surgical resection other than palliative debulking. Patients with metastasis to any organ at diagnosis were excluded from the analysis.
The primary outcome of interest was overall survival, captured as survival status (alive/dead and survival months). The study included only patients with complete data on margin status, survival, and follow- up time over one month. The analysis adjusted for patients’ de- mographic, socio-economic, tumor-related, adjuvant, and hormonal therapy receipt.
2.2. Statistical analysis
Descriptive statistics were computed for baseline characteristics stratified by margin status (R0 vs. R1/R2). The baseline differences be- tween the groups were determined using the Student’s t-test and Pearson chi-square test for continuous and categorical variables, respectively. The entire cohort’s 5- and 10-year overall survival were estimated using the Kaplan-Meier method. These survival estimates were also computed for patient sub-groups based on margin status, age, and tumor stage. A multivariable inverse-probability-weighted Cox Proportional Hazard model was used to estimate the effect of margin status on overall survival for the entire cohort, adjusting for measured confounders. Survival sta- tistics were presented in months and hazard ratio (i.e., the risk of death).
To evaluate the changes in survival and the associated impact of margin status on survival over time, we divided the sample into two cohorts based on the year of diagnosis: historical (2008-2012) and contemporary (2013-2017) cohorts. We chose a 2012 cut-off year to reflect the last analysis performed on this research topic by Anderson et al., which used the NCDB data spanning 1998 to 2012. Also, the 2008-2017 period provides similar numbers of patients in each 5-year cohort and a reasonable follow-up period to assess survival after 2017 (since our dataset ends in 2020). We then evaluated the differential adverse impact of positive margin status for patients diagnosed in the historical versus contemporary cohorts.
Furthermore, we introduced a cohort period variable in the multi- variable Cox Proportional Hazard model to evaluate any difference in overall survival between the historical (2008-2012) and contemporary (2013-2017) cohorts.
Lastly, using a multivariable logistic regression model, we evaluated the differential utilization of adjuvant therapy between the historical and contemporary cohorts and the combined impact of adjuvant treatment and margin status on survival. A composite variable specifying adjuvant therapy was created to indicate 1 if a patient received radiation or chemotherapy postoperatively and 0 otherwise. We used the R0 patients in the historical cohort as the baseline reference group to estimate the odds of adjuvant therapy receipt. This approach allowed us to evaluate how the odds of adjuvant treatment for R1/R2 patients changed over time relative to the baseline group in the historical cohort (R0 patients). We also included an interaction term between margin status (R0 vs. R1/
R2) and cohort period (historical vs. contemporary) in the logistic regression model. The coefficient of this interaction term thus estimates the change in the impact of margin status on adjuvant therapy utilization over time.
3. Results
3.1. Baseline characteristics
We identified 5023 patients with ACC diagnoses in the NCDB data- base between 2004 and 2020. Of these, 3195 patients (63.6 %) under- went surgical resections other than surgical debulking, of which 2213 patients (69.3 %) had an R0 resection. The entire cohort was 61.3 % females, with a mean age of 52.9 years, 86.6 % White, and 1342 (42 %) were alive by the end of the study period (Table 1).
3.2. Survival analysis
The entire cohort’s median overall survival (OS) was 55.6 months (95%CI 51.12-66.0). When stratified by margin status, the median OS was 78.8 months (95%CI 71.9-87.1) for RO margin compared to 22.9 months (95%CI 19.9-25.9) for patients with R1/R2 margin (Table 2).
The 1-year, 5-year, and 10-year OS for the entire cohort was 82 % (95%CI 81-83 %), 48.6 % (95%CI 46.7-50.5), and 35.6 % (95%CI 33.5-37.7), respectively (Fig. 1). In patients with RO resections, the 1- year, 5-year, and 10-year OS were 86.7 % (95%CI 85.1-88.1 %), 56.1 % (95%CI 53.8-58.4 %), and 41.2 % (95%CI 38.5-43.9 %), respectively. There was a statistically significant difference in the OS of patients with R0 compared to those with any positive margin (R1/R2) (Stratified Log- Rank test p = 0.006) (Fig. 2). Table 2 presents the Kaplan-Maier survival estimates for the entire cohort.
Using the multivariable and inverse-probability-weighted Cox Pro- portional Hazard model to adjust for confounding, the R1/R2 margin (compared to RO) had a higher mortality rate (HR 1.89 [95CI 1.50-2.40]) with an associated decrease in OS by 15.6 months (95CI 5.9-25.2, p = 0.002). In addition, compared to R0, mortality rates were higher for R1 (HR 1.84 [95CI 1.29-2.61]) and R2 patients (HR1.96 (95CI 1.48-2.60); however, there was no significant difference in the mortality comparing R1 to R2 patients (HR 1.07 [95CI: 0.71-1.61, p = 0.764]. (Table 2 and eTable 2). Of note is that the postoperative disease stage impacted OS (eTable 2). Furthermore, there was no detectable association between mortality and male sex/gender, race, ethnicity, insurance status, neigh- borhood status (i.e., level of education, median household income, or metro/urban/rural), facility type, distance from the hospital, lymph nodal status or surgical approach (eTable 2).
3.3. Trends & impact of surgical margins, treatment strategies, and survival over a decade
3.3.1. Baseline and overall survival indices
The overall baseline characteristics of patients in this 10-year period (2008-2017) were similar to those of the entire cohort (2004-2020)- see eTable1. In the contemporary cohort (2008-2012), the proportion of patients with documented R0 margins increased slightly to 68.9 % compared to 67.6 % in the historical cohort (eTable1). The survival analysis showed no significant difference in overall survival comparing patients treated in the historical versus contemporary cohorts (Table 3).
3.3.2. Impact of surgical margin status on survival trends
In evaluating the trend and impact of margin status over time, we restricted the analysis to a 10-year period of two 5-year cohorts (see rationale in the method section).
Survival analysis within this 10-year sample cohort showed that although the adverse impact of positive surgical margin (R1/R2) on overall survival was consistent across the 10-year period (HR 2.04 95CI 1.59-2.63), it decreased over time (Table 3). For the 2008-2012 cohort,
| Variables | R0 | R1/R2 | Unknown | Total | p-value |
|---|---|---|---|---|---|
| N =2213 | N = 567 | N = 415 | N = 3195 | ||
| Alive | 1063 (51.1 %) | 156 (29.4 %) | 123 (31.1 %) | 1342 (44.6 %) | <0.001 |
| Mean Age (SD) | 52.6 (16.8) | 53.3 (17.1) | 54.3(16.6) | 52.9(16.9) | 0.14 |
| Age Categories | 0.13 | ||||
| <45 years | 653 (29.7 %) | 168 (29.7 %) | 104 (25.1 %) | 925 (29.1 %) | |
| 45-54 years | 454 (20.6 %) | 103 (18.2 %) | 96 (23.2 %) | 653 (20.5 %) | |
| 55-64 years | 518 (23.6 %) | 135 (23.9 %) | 83 (20.0 %) | 736 (23.2 %) | |
| 65-74 years | 398 (18.1 %) | 106 (18.7 %) | 92 (22.2 %) | 596 (18.7 %) | |
| ≥75 years | 176 (8.0 %) | 54 (9.5 %) | 39 (9.4 %) | 269 (8.5 %) | |
| SEX | 0.17 | ||||
| Female | 1356 (61.3 %) | 363 (64.0 %) | 241 (58.1 %) | 1960 (61.3 %) | |
| Race Groups | 0.064 | ||||
| White | 1916 (86.6 %) | 485 (85.5 %) | 345 (83.1 %) | 2746 (85.9 %) | |
| Black | 202 (9.1 %) | 54 (9.5 %) | 39 (9.4 %) | 295 (9.2 %) | |
| Others | 78 (3.5 %) | 22 (3.9 %) | 21 (5.1 %) | 121 (3.8 %) | |
| Unknown | 17 (0.8 %) | 6 (1.1 %) | 10 (2.4 %) | 33 (1.0 %) | |
| Ethnicity | 0.013 | ||||
| non-Hispanic | 1989 (89.9 %) | 497 (87.7 %) | 361 (87.0 %) | 2847 (89.1 %) | |
| Unknown | 87 (3.9 %) | 17 (3.0 %) | 25 (6.0 %) | 129 (4.0 %) | |
| Charles-Dayo Comorbid Score | <0.35 | ||||
| CD Score 0 | 1672 (75.6 %) | 406 (71.6 %) | 320 (77.1 %) | 2398 (75.1 %) | |
| CD Score 1 | 397 (17.9 %) | 111 (19.6 %) | 68 (16.4 %) | 576 (18.0 %) | |
| CD Score 2 | 91 (4.1 %) | 29 (5.1 %) | 16 (3.9 %) | 136 (4.3 %) | |
| CD Score 3 | 53 (2.4 %) | 21 (3.7 %) | 11 (2.7 %) | 85 (2.7 %) | |
| Surgical Approach | 0.26 | ||||
| Open | 889 (64.9 %) | 220 (65.5 %) | 116 (61.4 %) | 1225 (64.6 %) | |
| Laparoscopic | 326 (23.8 %) | 90 (26.8 %) | 50 (26.5 %) | 466 (24.6 %) | |
| Robotic assisted | 155 (11.3 %) | 26 (7.7 %) | 23 (12.2 %) | 204 (10.8 %) | |
| Regional LN Status | <0.001 | ||||
| Negative Reg Node | 444 (20.1 %) | 92 (16.2 %) | 53 (12.8 %) | 589 (18.4 %) | |
| 1-5 positive node | 83 (3.8 %) | 42 (7.4 %) | 12 (2.9 %) | 137 (4.3 %) | |
| ≥6 positve nodes | 80 (3.6 %) | 34 (6.0 %) | 39 (9.4 %) | 153 (4.8 %) | |
| No nodes examined | 1606 (72.6 %) | 399 (70.4 %) | 311 (74.9 %) | 2316 (72.5 %) | |
| Hormone Therapy | 0.52 | ||||
| Yes | 65 (2.9 %) | 24 (4.2 %) | 15 (3.6 %) | 104 (3.3 %) | |
| Unknown | 16 (0.7 %) | 3 (0.5 %) | 4 (1.0 %) | 23 (0.7 %) | |
| Chemotherapy | <0.001 | ||||
| Yes | 775 (35.0 %) | 266 (46.9 %) | 168 (40.5 %) | 1209 (37.8 %) | |
| Unknown | 48 (2.2 %) | 10 (1.8 %) | 13 (3.1 %) | 71 (2.2 %) | |
| Radiation Therapy | <0.001 | ||||
| Yes | 342 (15.5 %) | 183 (32.3 %) | 71 (17.1 %) | 596 (18.7 %) | |
| Unknown | 65 (2.9 %) | 18 (3.2 %) | 15 (3.6 %) | 98 (3.1 %) | |
| Median Household Income | 0.56 | ||||
| > $57,856 | 1209 (63.3 %) | 303 (62.9 %) | 219 (60.3 %) | 1731 (62.8 %) | |
| Percent No High School Diploma | 0.86 | ||||
| >15.2 % | 375 (19.6 %) | 90 (18.6 %) | 76 (20.7 %) | 541 (19.6 %) | |
| 9.1 %-15.2 % | 529 (27.6 %) | 143 (29.5 %) | 97 (26.4 %) | 769 (27.8 %) | |
| 5 %-9 % | 574 (30.0 %) | 133 (27.5 %) | 108 (29.4 %) | 815 (29.5 %) | |
| <5 % | 436 (22.8 %) | 118 (24.4 %) | 86 (23.4 %) | 640 (23.1 %) | |
| Insurance Status at Diagnosis | <0.001 | ||||
| Uninsured | 79 (3.6 %) | 22 (3.9 %) | 20 (4.8 %) | 121 (3.8 %) | |
| Private Insurance/Managed Care | 1261 (57.0 %) | 312 (55.0 %) | 212 (51.1 %) | 1785 (55.9 %) | |
| Medicaid | 206 (9.3 %) | 46 (8.1 %) | 18 (4.3 %) | 270 (8.5 %) | |
| Medicare | 595 (26.9 %) | 162 (28.6 %) | 119 (28.7 %) | 876 (27.4 %) | |
| Other Government | 42 (1.9 %) | 13 (2.3 %) | 2 (0.5 %) | 57 (1.8 %) | |
| Unknown | 30 (1.4 %) | 12 (2.1 %) | 44 (10.6 %) | 86 (2.7 %) | |
| Facility Type | 0.006 | ||||
| Community Cancer Program | 56 (3.2 %) | 20 (4.5 %) | 12 (3.4 %) | 88 (3.5 %) | |
| Comp Comm Cancer Prog | 425 (24.4 %) | 102 (23.0 %) | 113 (32.5 %) | 640 (25.3 %) | |
| Academic/Research Prog | 988 (56.7 %) | 235 (53.0 %) | 165 (47.4 %) | 1388 (54.8 %) | |
| Integ Network Cancer Prog | 272 (15.6 %) | 86 (19.4 %) | 58 (16.7 %) | 416 (16.4 %) | |
| Geographical location | 0.39 | ||||
| Metro area | 1754 (84.1 %) | 474 (87.3 %) | 323 (85.7 %) | 2551 (84.9 %) | |
| Urban area | 286 (13.7 %) | 62 (11.4 %) | 47 (12.5 %) | 395 (13.1 %) | |
| Rural area | 45 (2.2 %) | 7 (1.3 %) | 7 (1.9 %) | 59 (2.0 %) |
(continued on next page)
| Variables | R0 | R1/R2 | Unknown | Total | p-value |
|---|---|---|---|---|---|
| N = 2213 | N = 567 | N = 415 | N = 3195 | ||
| Distance from Treatment Facility | 0.074 | ||||
| <10 miles | 678 (35.1 %) | 192 (39.6 %) | 152 (40.8 %) | 1022 (36.6 %) | |
| 10 -50miles | 818 (42.3 %) | 198 (40.8 %) | 136 (36.5 %) | 1152 (41.3 %) | |
| >50 miles | 438 (22.6 %) | 95 (19.6 %) | 85 (22.8 %) | 618 (22.1 %) |
| Cohort | Overall Survival | |||
|---|---|---|---|---|
| Mediana | 1-Year | 5-Year | 10-Year | |
| Entire | 55.6 | 82.0 % | 48.6 % | 35.6 % |
| R0 | 78.8 | 86.7 % | 56.1 % | 41.2 % |
| R1 | 26.6 | 70.1 % | 34.2 % | 24.5 % |
| R2 | 18.9 | 63.0 % | 26.9 % | 18.6 % |
| R1/R2 | 22.9 | 67.1 % | 31.0 % | 21.9 % |
B. Adjusted Survival Estimates
| Cohort | Survival | ||||
|---|---|---|---|---|---|
| Meanª | 95%CI | HR | 95%CI | p- value | |
| R0 | 40.8 | 35.6-46.0 | Ref | – | – |
| R1 | 31.2 | 19.8-42.5 | 1.90 | 1.46-2.57 | <0.001 |
| R2 | 16.9 | 9.7-24.0 | 1.88 | 1.35-2.62. | <0.001 |
| R1/R2 | 25.2 | 17.4-33.0 | 1.89 | 1.50-2.40 | <0.001 |
C. Adjusted Survival Estimate with Positive margins (reference group: R2)
| Cohort | HR | 95 % CI. | p-value |
|---|---|---|---|
| R1 | 1.04 | 0.70-1.54. | 0.841 |
a
In months.
a positive margin increased mortality risk by 129 % (HR 2.29, 95CI 1.47-3.58), compared to a 97 % increase in the 2013-2017 cohort (HR 1.97, 95CI 1.40-2.80). However, being treated in either cohort period did not impact survival (HR 0.99, 95CI 1.41-3.04) (Table 3).
3.3.3. Trends in adjuvant therapy utilization & its survival impact across margin status
In the historical cohort (2008-2012), the odds of receiving adjuvant therapy (i.e., radiation, chemotherapy, or both) were significantly higher for R1/R2 (OR 2.64, p < 0.001). In the contemporary cohort, these odds decreased but remained significant (OR 1.7, p = 0.03) (Table 4).
Adjuvant therapy use in R1/R2 margin patients was associated with a decreased mortality (HR 0.45 (95%CI 0.29-0.72, p < 0.001). These findings demonstrate change in the use of adjuvant therapy over time for ACC patients with positive margins (Table 4).
4. Discussion
Current guidelines recommend an R0 resection for localized and recurrent disease when feasible to achieve improved survival out- comes.10,19,20 Studies examining survival in ACC have shown an associ- ation between positive margins and worse survival.5,15 Our study findings reaffirm the literature’s finding of the critical importance of achieving a negative surgical margin to improve survival outcomes. Furthermore, when evaluating the effect of adjuvant therapy on survival, we found a substantial reduction in mortality risk among R1/R2 patients, which highlights the effectiveness of adjuvant therapy in this group of patients - in line with current guidelines. However, we found no survival benefit of adjuvant therapy for patients with R0 resection margins. In fact, there was a slightly increased but not statistically significant risk of mortality among R0 margin patients who received adjuvant therapy.
To our knowledge, there is limited data examining survival trends of surgically treated ACC patients over time. Additionally, the current
Kaplan-Meier survival estimate
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0.75
Percent Survive
0.50
0.25
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48
60
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96
108
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132 144
156
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220 204
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Survival Time (Months)
Kaplan-Meier survival estimates
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0.75
Log-rank p-value = 0.006
Survival Probability
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Negative (RO) margin
Positive (R1/R2) margin
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50
100
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Survival Time (in months)
Kaplan-Meier survival estimates
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Log-rank p-value = 0.01
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RO margin
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R1 margin
R2 margin
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Survival time (in months)
| Patient group | Mortality Risk (HR: R1/R2 vs R0) |
|---|---|
| R1/R2 vs R0 | 2.04ª |
| HC (2008-2012) | 2.29ª |
| CC (2013-2017) | 2.04ª |
| HC vs CC | 0.99 |
| Adjuvant therapy | 0.91 |
| RO margin + Adjuvant therapy | 1.08 |
| R1/R2 margin + Adjuvant therapy | 0.45ª |
a Statistically significant. HC: historical cohort, CC: contemporary cohort. R0 margin: negative margin. R1/R2 margin: positive margin.
| Categories | Adjuvant therapy Utilization (OR: R1/R2 vs R0) | Proportion receiving adjuvant therapy (%) | |
|---|---|---|---|
| R0 margin | R1/R2 margin | ||
| 2008-2017 | 1.86ª | 44.3 | 63.2 |
| HC | 2.64ª | 43.6 | 61.1 |
| (2008-2012) | |||
| CC (2013-2017) | 1.70ª | 44.9 | 65.3 |
| CC X R0 margin | 1.03 | ||
| CC X R1/R2 | 1.76ª | ||
| margin | |||
| HC X R1/R2 | 2.20ª | ||
| margin | |||
HC: historical cohort, CC: contemporary cohort. CC x R0 is an interaction be- tween the contemporary cohort and the R0 margin, CC x R1/R2 is an interaction between the contemporary cohort and the R1/R2 margin, and HCx R1/R2 is an interaction between the historical cohort and the R1/R2 margin.
a Statistically significant. R0 margin: negative margin. R1/R2 margin: positive margin.
understanding of the temporal trend and impact of surgical margin sta- tus, independently and combined with adjuvant therapy utilization, is even more limited. Most studies examining the role of adjuvant therapy after adrenal surgery for low-risk ACC have focused on mitotane17,18,21,22 or radiotherapy23 with little or no consideration for the surgical margins’ status. Our analysis revealed that there has been a slight improvement in achieving a negative margin over the years, with R0 rates of 68.9 % in the contemporary cohort versus 67.6 % in the historical cohort. This trend may be attributed to possible improvements in surgical techniques over time. We also observed a decreasing trend in the adverse impact of a positive margin on the survival of ACC patients over the period studied, with a lower risk of death from an R1/R2 margin in the contemporary cohort (HR 1.7) compared to the historical cohort (HR 2.29) (Table 3). To further evaluate this trend, we examined the contributory impact of adjuvant therapy, given the possibility of changes in clinical practice protocols and the higher likelihood of receiving adjuvant therapy over the same period. Here, we observed that although there has been an overall upward trend in administering adjuvant therapy to ACC patients, this trend seemed higher in R1/R2 margin patients (Table 4). However, adjuvant therapy was only associated with a survival benefit in R1/R2 margin patients (Table 3). Further, our analysis showed a slight increase in mortality in R0 patients who received adjuvant therapy compared to their peers who did not (Table 3).
Together, these findings highlight three clinically relevant points with potential implications for future clinical guidelines. First, the increasing use of adjuvant therapy in R1/R2 patients may explain the decreasing survival gap observed between R0 and R1/R2 patients over time (Table 3). Second, the primary benefit of adjuvant therapy may only
be in cases where surgical resection alone is insufficient, similar to those reported by Skertich et al.15 Lastly, the slight increase in the mortality risk of R0 patients who received adjuvant therapy may indicate over— treatment- though this finding was not statistically significant.
Interestingly, we did not observe any difference in overall survival between patients treated in the historical and contemporary cohort, suggesting that the survival rates of surgically treated ACC patients have remained largely unchanged over the decade. This finding may seem counterintuitive given the aforementioned increase in adjuvant therapy utilization and improvement in achieving surgical margins. However, there are a few possible explanations for this observation. First, the stage of disease presentation has likely remained similar across the cohort, thus providing limited room for improvement in survival despite improve- ment in margins and adjuvant therapy. Additionally, there is a large amount of missing data in the NCDB that captures the stage of disease, which thwarts our analysis’s ability to examine this phenomenon. Sec- ond, it is possible that the improvements in surgical margins and adju- vant therapy utilization might require time to translate into measurable survival impact - the so-called treatment lag effect.24 The third reason relates to the potential issue of unmeasured confounding, such as genetic and other factors, which may bias the survival estimates when not controlled for in the analysis. Lastly, given that ACC is an aggressive disease, modest advancement in surgical margins and adjuvant treatment might be insufficient to alter the course of the disease.
4.1. Study limitations
Our study has several limitations. Firstly, this study used a retro- spective large registry database, which introduces limitations, such as patient selection bias, missing data, and attrition. We have tried to minimize this selection bias using an inverse probability-weighted approach to assign treatment selection for the Cox survival model. Sec- ondly, the NCDB does not capture some factors, such as the specifics of tumor pathology and timing of adjuvant therapy, that may play an essential role in survival. Thirdly, we sought to examine temporal trends in treatment for ACC, exploring a historical and contemporary cohort. However, these cohorts were chosen based on data availability, which could introduce bias within the analysis. Prospective studies are needed to confirm our results and explore the underlying mechanisms for the observed trends. Lastly, despite using a large, national database, the findings of this study may not be generalizable given potential differ- ences in patient, surgeon, and environmental factors that are not accounted for in our analysis.
5. Conclusion
A positive surgical margin status adversely and significantly impacts overall survival for patients with ACC. Despite improvements in both the rates of R0 margins after surgery and the utilization of adjuvant therapy over the years, overall survival has not improved considerably. The analysis did not observe any significant difference in overall survival between patients treated in the historical and contemporary cohort, demonstrating that survival rates of surgically treated ACC patients show limited improvement over the study period. This finding highlights the need for treatment advances for ACC to improve overall survival.
CRediT authorship contribution statement
Kelvin Memeh: Software, Methodology, Investigation, Data cura- tion. Sara Abou Azar: Writing - review & editing, Writing - original draft, Software, Resources, Methodology, Investigation, Formal analysis, Conceptualization. Oluwasegun Afolaranmi: Writing - review & edit- ing, Writing - original draft, Resources, Methodology, Investigation, Formal analysis, Conceptualization. Tanaz M. Vaghaiwalla: Writing - review & editing, Writing - original draft.
Declaration of competing interest
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors declare that they have no conflict of interest.
Acknowledgement
The data used in the study are derived from a de-identified NCDB file. The American College of Surgeons and the Commission on Cancer have not verified and are not responsible for the analytic or statistical meth- odology employed, or the conclusions drawn from these data by the investigator.
References
1. Sharma E, et al. The characteristics and trends in adrenocortical carcinoma: a United States population based study. J Clin Med Res. 2018;10(8):636-640.
2. Tierney JF, Chivukula SV, Poirier J, et al. National treatment practice for adrenocortical carcinoma: have they changed and have we made any progress? J Clin Endocrinol Metab. 2019;104(12):5948-5956. https://doi.org/10.1210/jc.2019- 00915.
3. Shah M, et al. Surgical resection for adrenocortical carcinoma: current trends affecting survival. J Surg Oncol. 2022;125(8):1224-1230.
4. Kebebew E, et al. Extent of disease at presentation and outcome for adrenocortical carcinoma: have we made progress? World J Surg. 2006;30(5):872-878.
5. Anderson Jr KL, et al. Impact of micro- and macroscopically positive surgical margins on survival after resection of adrenocortical carcinoma. Ann Surg Oncol. 2018;25(5): 1425-1431.
6. SEER*Explorer. An interactive website for SEER cancer statistics [Internet]. Surveillance Research Program, National Cancer Institute. [cited 2023 February 23]; Available from: https://seer.cancer.gov/explorer/.
7. Margonis GA, Kim Y, Prescott JD, et al. Adrenocortical carcinoma: impact of surgical margin status on long-term outcomes. Ann Surg Oncol. 2016;23(1):134-141. https:// doi.org/10.1245/s10434-015-4803-x.
8. Fassnacht M, et al. Combination chemotherapy in advanced adrenocortical carcinoma. N Engl J Med. 2012;366(23):2189-2197.
9. Shah MH, et al. Neuroendocrine and adrenal tumors, version 2.2021, NCCN clinical practice guidelines in Oncology. J Natl Compr Cancer Netw. 2021;19(7):839-868.
10. Gaujoux S, et al. European society of endocrine surgeons (ESES) and European network for the study of adrenal tumours (ENSAT) recommendations for the surgical management of adrenocortical carcinoma. Br J Surg. 2017;104(4):358-376.
11. Huynh KT, et al. Impact of laparoscopic adrenalectomy on overall survival in patients with nonmetastatic adrenocortical carcinoma. J Am Coll Surg. 2016;223(3):485-492.
12. Tella SH, et al. Predictors of survival in adrenocortical carcinoma: an analysis from the national cancer database. J Clin Endocrinol Metab. 2018;103(9):3566-3573.
13. Libe R, Huillard O. Adrenocortical carcinoma: diagnosis, prognostic classification and treatment of localized and advanced disease. Cancer Treat Res Commun. 2023;37: 100759.
14. Hermanek P, Wittekind C. Residual tumor (R) classification and prognosis. Semin Surg Oncol. 1994;10(1):12-20.
15. Skertich NJ, et al. Risk factors associated with positive resection margins in patients with adrenocortical carcinoma. Am J Surg. 2020;220(4):932-937.
16. Ginsburg KB, et al. Association of surgical approach with treatment burden, oncological effectiveness, and perioperative morbidity in adrenocortical carcinoma. Clin Genitourin Cancer. 2022;20(5):497 e1-e497 e7.
17. Berruti A, et al. Long-term outcomes of adjuvant mitotane therapy in patients with radically resected adrenocortical carcinoma. J Clin Endocrinol Metab. 2017;102(4): 1358-1365.
18. Tang Y, et al. Benefits of adjuvant mitotane after resection of adrenocortical carcinoma: a systematic review and meta-analysis. BioMed Res Int. 2018;2018: 9362108.
19. Fassnacht M, et al. Adrenocortical carcinomas and malignant phaeochromocytomas: ESMO-EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2020;31(11):1476-1490.
20. Yip L, Duh QY, Wachtel H, et al. American association of endocrine surgeons guidelines for adrenalectomy: executive summary. JAMA Surg. 2022 Oct 1;157(10): 870-877. https://doi.org/10.1001/jamasurg.2022.3544. PMID: 35976622; PMCID: PMC9386598.
21. Terzolo M, Fassnacht M, Perotti P, et al. Adjuvant mitotane versus surveillance in low-grade, localised adrenocortical carcinoma (ADIUVO): an international, multicentre, open-label, randomised, phase 3 trial and observational study. Lancet Diabetes Endocrinol. 2023;11(10):720-730. https://doi.org/10.1016/S2213- 8587(23)00193-6 [published correction appears in Lancet Diabetes Endocrinol. 2023 Dec;11(12):e14. doi: 10.1016/S2213-8587(23)00319-4].
22. Tang Y, Liu Z, Zou Z, Liang J, Lu Y, Zhu Y. Benefits of adjuvant mitotane after resection of adrenocortical carcinoma: a systematic review and meta-analysis. BioMed Res Int. 2018;2018:9362108. https://doi.org/10.1155/2018/9362108. Published 2018 Jun 4.
23. Viani GA, Viana BS. Adjuvant radiotherapy after surgical resection for adrenocortical carcinoma: a systematic review of observational studies and meta-analysis. J Cancer Res Therapeut. 2019;15(Supplement):S20-S26. https://doi.org/10.4103/jcrt.JCRT_ 996_15.
24. Park K, Qiu P. Evaluation of the treatment time-lag effect for survival data. Lifetime Data Anal. 2018;24(2):310-327. https://doi.org/10.1007/s10985-017-9390-7.