Abstract
Objective:
To compare 30-day postoperative complications for patients with advanced ovarian cancer who underwent resection to no gross residual disease versus optimal and suboptimal cytoreduction.
Methods:
A retrospective cohort study of women drawn from the National Surgical Quality Improvement Program who underwent cytoreductive surgery for advanced ovarian cancer between 2014 and 2019 was performed. Exposure of interest was extent of surgical resection defined as no gross residual disease; residual disease <1cm (optimal); and residual disease >1cm (suboptimal). Primary outcome was postoperative complication. Associations were examined with bivariable tests and multivariable logistic regression.
Results:
A total of 2,248 women underwent cytoreductive surgery; 68.4% (n=1,538) underwent resection to no gross residual disease, 22.4% (n=504) had an optimal, and 9.2% (n=206) had a suboptimal cytoreduction. Optimal cytoreduction patients had the highest rates of any postoperative complication (35.5%, p<0.001). They also had the longest operative times and procedures that were most surgically complex (203 min, 43.6 relative value units, both p<0.05). However, patients who underwent optimal cytoreduction did not have increased odds of major complications (aOR 1.20, 95%CI 0.91–1.58).
Conclusion:
Patients who underwent optimal cytoreduction had more postoperative complications, required the most operating room time, and represented more complex surgeries compared with suboptimal cytoreduction or resection to no gross residual disease.
Keywords: Cytoreduction, Optimal, Ovarian cancer, Debulking, Suboptimal, No gross residual
INTRODUCTION
Cytoreductive surgery is a cornerstone of ovarian cancer treatment and a key factor in patient survival.1,2 Cytoreduction, or debulking, involves resection of all visible tumor. The extent of resection achieved during debulking hinges on multiple factors including surgical effort, tumor location, and tumor biology.3,4 Complete cytoreduction to no gross residual (NGR) disease is associated with significant prolongation of life.5,6 Another desirable outcome is optimal resection – leaving behind no residual tumor measuring larger than 1 centimeter in diameter. If complete cytoreduction to NGR disease is not attainable, optimal cytoreduction is the goal.7 If residual tumor greater than 1 centimeter in diameter remains after surgery, the outcome is considered suboptimal.
Postoperative complications in the first 30 days after debulking surgery can delay chemotherapy, or result in dose reduction, and both can lead to inferior survival.8 A National Cancer Database study of women with ovarian cancer demonstrated chemotherapy delays greater than 35 days after cytoreductive surgery were associated with a 7% increased hazard of death, compared with women who began chemotherapy during the recommended 21–35 days following surgery.9 Currently, the goals of cytoreductive surgery are to achieve NGR with optimal cytoreduction as an additional acceptable outcome. Apart from the effects of surgical debulking on survival, which are well documented, little is known about the association between residual disease at the end of surgery and postoperative complications. Aggressive cytoreductive surgery is associated with an increased risk of postoperative complications.10,11 This is likely due to the radicality required to achieve a resection to NGR or optimal cytoreductive surgery.
Our objective was to evaluate the association between residual disease at the conclusion of surgery and 30-day postoperative complications among patients with advanced ovarian cancer who underwent cytoreductive surgery in a large national quality database. Understanding these associations may improve surgical decision-making and postoperative management for contemporary patients with advanced ovarian cancer.
MATERIALS AND METHODS
A retrospective cohort study of women who underwent cytoreductive surgery recorded in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) was performed. NSQIP is a national quality database that collects preoperative, intraoperative and postoperative data. Hospitals that voluntarily participate in the database are given access to data regarding their own procedures to drive quality improvement.12 Data are abstracted by trained clinical reviewers and audited regularly. For an institution’s data to be used in the nationally available file, interobserver agreement during an audit must be greater than 95% and averages 98% for included sites.13 Within NSQIP, there is a targeted hysterectomy file that includes preoperative, intraoperative, and postoperative variables specific to hysterectomy.14 This study was reviewed by the Institutional Review Board and deemed exempt from formal review as the data is deidentified.
Our cohort included women in both the hysterectomy specific file and general NSQIP file between 2014 and 2019, which were linked. Patients who underwent cytoreductive surgery for ovarian cancer were identified using the cancer case variable and international classification of disease 9 and 10 codes for ovarian cancer (ICD-9 code 183.0 and ICD-10 code 56.9). Only patients with advanced stage disease (IIIB or greater) were included. Current procedural terminology (CPT) codes were used to identify patients who underwent cytoreductive surgery (CPT codes 58943, 58950, 58951, 58952, 58953, 58954, 58956). Surgeries performed by specialists who were not gynecologists and further by those who were not gynecologic oncologists, subspecialists with additional training in cytoreductive techniques, were excluded.
Demographic variables abstracted included age, race, body mass index (BMI) and parity. Patient-related pre-operative variables included hypertension requiring medication, diabetes requiring insulin or oral therapy, congestive heart failure in the 30 days preceding surgery, smoking in the last year and weight loss greater than 10% of total body weight in the 6 months before surgery. Preoperative lab values included: albumin, creatinine, white blood cell count (WBC), hematocrit, platelet count and serum sodium. Operative variables included preoperative disease location, residual disease location, operative time, year operation was performed, relative value units (RVUs), and American Society of Anesthesiologists (ASA) score. Postoperative variables included stage, time from operation to discharge, and presence of major and minor complications. Major complication, as described previously,15 was a composite outcome that included: need for readmission, need to return to the operating room, cardiac arrest, myocardial infarction, stroke or cerebrovascular accident, renal failure, venous thromboembolism, deep venous thrombosis, pulmonary embolus, sepsis, septic shock, pneumonia, organ space surgical site infection, deep surgical site infection, ventilation necessary for >48 hours, unplanned need for reintubation, intestinal obstruction, anastomotic leak, ureteral obstruction, bladder fistula, and ureteral fistula. Minor complication, as described previously,15 was a composite outcome that included: blood transfusion, urinary tract infection, wound disruption, clostridium difficile infection, prolonged postoperative course and superficial surgical site infection. Any complication included all major and minor complications. Detailed definitions of each complication can be found in the NSQIP user guide12.
The exposure of interest – extent of residual disease – was defined as follows: no gross residual (NGR) disease, residual disease <1 cm (optimal), and residual disease > 1cm (suboptimal). The primary outcomes were major, minor and any postoperative complication.16 A composite incidence of any complication was compared between patients, stratified by extent of residual disease. This was similarly performed for minor and major complication. Categorical variables were represented by frequency and percentage, while continuous variables were represented by median and interquartile range (IQR). Differences in categorical variables were determined using Chi-Square tests. Differences in continuous variables were determined using ANOVA and Kruskal-Wallis for nonparametric variables. Given the association of demographic and clinical factors with complications and extent of residual disease, logistic regression was performed to address the possibility of confounding. All variables that were significantly associated with extent of residual disease or complications on univariate analysis were examined. The exposure of interest, extent of residual disease, was also compared with respect to additional secondary outcomes, including surgical complexity and operative time. All p-values were two sided with p<0.05 considered significant. Stata version 17.0 (College Station, TX) was used for all analyses.
RESULTS
We identified 2,248 women who underwent cytoreductive surgery for advanced ovarian cancer between 2014 and 2019. Among these patients, 1,538 (68.4%) underwent resection to NGR disease, 504 (22.4%) underwent optimal resection and 206 (9.2%) underwent suboptimal resection. Patient characteristics are described in Table 1. Patients who had NGR disease were less likely to have lost >10% of their body weight in the six months preceding surgery (5.6% versus 8.1% and 12.6%, p<0.001). These patients were more likely to be White (72.4% versus 68.1% and 67.5%) or Asian (3.8% versus 2.6% and 2.9%) and less likely to be Hispanic compared with those who had an optimal or suboptimal resection (3.7% versus 4.8% and 5.3%, p<0.001). Patients who had NGR disease were also more likely to have stage IIIB disease (16.8% versus 9.7% and 9.2%) and lower preoperative platelet (294 versus 308 and 330) and white blood cell counts (7.0 versus 7.1 and 7.7, all p<0.001).
Table 1:
Associations between patient characteristics and extent of residual disease
| Overall N = 2,248 |
NGR N = 1,538 (68.4) |
Optimal N = 504 (22.4) |
Suboptimal N = 206 (9.2) |
p-value | |
|---|---|---|---|---|---|
|
| |||||
| Age (years) | |||||
| 18–29 | 24 (1.1) | 22 (1.4) | 1 (0.2) | 1 (0.5) | |
| 30–39 | 44 (2.0) | 31 (2.0) | 8 (1.6) | 5 (2.4) | |
| 40–49 | 223 (9.9) | 145 (9.4) | 49 (9.7) | 29 (14.1) | |
| 50–59 | 542 (24.1) | 386 (25.1) | 117 (23.2) | 39 (18.9) | 0.16 |
| 60–69 | 766 (34.1) | 528 (34.3) | 175 (34.7) | 63 (30.6) | |
| 70–79 | 521 (23.2) | 344 (22.4) | 120 (23.8) | 57 (27.7) | |
| 80+ | 123 (5.5) | 79 (5.1) | 33 (6.6) | 11 (5.3) | |
| Unknown | 5 (0.2) | 3 (0.2) | 1 (0.2) | 1 (0.5) | |
|
| |||||
| BMI (kg/m2) | 0.88 | ||||
| <18.5 | 27 (1.2) | 21 (1.4) | 4 (0.8) | 2 (1.0) | |
| 18.5–24.9 | 668 (29.7) | 471 (30.6) | 141 (28.0) | 56 (27.2) | |
| 25–29.9 | 707 (31.5) | 473 (30.8) | 166 (32.9) | 68 (33.0) | |
| 30–34.9 | 449 (20.0) | 310 (20.2) | 100 (19.8) | 39 (18.9) | |
| 35–39.9 | 216 (9.6) | 141 (9.2) | 53 (10.5) | 22 (10.7) | |
| 40–49.9 | 123 (5.5) | 84 (5.5) | 26 (5.2) | 13 (6.3) | |
| 50–100 | 17 (0.8) | 12 (0.8) | 5 (1.0) | 0 (0.0) | |
| Unknown | 41 (1.8) | 26 (1.7) | 9 (1.8) | 6 (2.9) | |
|
| |||||
| >10% weight loss in preceding 6 months | 153 (6.8) | 86 (5.6) | 41 (8.1) | 26 (12.6) | <0.001 |
|
| |||||
| Race | <0.001 | ||||
| White | 1,595 (71.0) | 1,113 (72.4) | 343 (68.1) | 139 (67.5) | |
| Black | 114 (5.1) | 89 (5.8) | 14 (2.8) | 11 (5.3) | |
| Asian | 77 (3.4) | 58 (3.8) | 13 (2.6) | 6 (2.9) | |
| Unknown | 462 (20.6) | 278 (18.1) | 134 (26.6) | 50 (24.3) | |
|
| |||||
| Hispanic | <0.001 | ||||
| Yes | 92 (4.1) | 57 (3.7) | 24 (4.8) | 11 (5.3) | |
| No | 1,748 (77.8) | 1,237 (80.4) | 361 (71.6) | 150 (72.8) | |
| Unknown | 408 (18.2) | 244 (15.9) | 119 (23.6) | 45 (21.8) | |
|
| |||||
| Hypertension | 875 (38.9) | 580 (37.7) | 210 (41.7) | 85 (41.3) | 0.22 |
|
| |||||
| Smoking | 257 (11.4) | 171 (11.1) | 60 (11.9) | 26 (12.6) | 0.76 |
|
| |||||
| Diabetes | 229 (10.2) | 161 (10.5) | 45 (8.9) | 23 (11.2) | 0.54 |
|
| |||||
| Congestive heart failure in preceding 30 days | 2 (0.1) | 2 (0.1) | 0 (0.0) | 0 (0.0) | 0.63 |
|
| |||||
| ASA score | 0.03 | ||||
| 1 | 36 (1.6) | 22 (1.4) | 6 (1.2) | 8 (3.9) | |
| 2 | 691 (30.7) | 457 (29.7) | 162 (32.1) | 72 (35.0) | |
| 3 | 1,367 (60.8) | 960 (62.4) | 291 (57.7) | 116 (56.3) | |
| 4+ | 153 (6.8) | 98 (6.4) | 45 (8.9) | 10 (4.9) | |
| Unknown | 1 (0.0) | 1 (0.1) | 0 (0.0) | 0 (0.0) | |
|
| |||||
| Prior abdominal surgery | 612 (27.2) | 420 (27.3) | 136 (27.0) | 56 (27.2) | 0.99 |
|
| |||||
| Prior pelvic surgery | 1,110 (49.4) | 748 (48.6) | 255 (50.6) | 107 (51.9) | 0.55 |
|
| |||||
| Parity | 0.66 | ||||
| 0 | 582 (25.9) | 400 (26.0) | 133 (26.4) | 49 (23.8) | |
| 1 | 360 (16.0) | 253 (16.5) | 76 (15.1) | 31 (15.1) | |
| 2 | 695 (30.9) | 481 (31.3) | 155 (30.8) | 59 (28.6) | |
| 3+ | 611 (27.2) | 404 (26.3) | 140 (27.8) | 67 (32.5) | |
|
| |||||
| Stage | <0.001 | ||||
| IIIB | 326 (14.5) | 258 (16.8) | 49 (9.7) | 19 (9.2) | |
| IIIC | 1,520 (67.6) | 1,012 (65.8) | 354 (70.2) | 154 (74.8) | |
| IV | 402 (17.9) | 268 (17.4) | 101 (20.0) | 33 (16.0) | |
|
| |||||
| Year of operation | 0.35 | ||||
| 2014 | 249 (11.1) | 163 (10.6) | 56 (11.1) | 30 (14.6) | |
| 2015 | 278 (12.4) | 188 (12.2) | 63 (12.5) | 27 (13.1) | |
| 2016 | 368 (16.4) | 261 (17.0) | 80 (15.9) | 27 (13.1) | |
| 2017 | 450 (20.0) | 300 (19.5) | 117 (23.2) | 33 (16.0) | |
| 2018 | 428 (19.0) | 298 (19.4) | 91 (18.1) | 39 (18.9) | |
| 2019 | 475 (21.1) | 328 (21.3) | 97 (19.2) | 50 (24.3) | |
|
| |||||
| Pre-operative albumin | 3.8 (0.5) | 3.8 (0.5) | 3.8 (0.5) | 3.7 (0.6) | <0.001 |
|
| |||||
| Pre-operative creatinine | 0.78 (0.34) | 0.79 (0.39) | 0.77 (0.19) | 0.77 (0.23) | 0.37 |
|
| |||||
| Pre-operative WBC | 7.1 (3.2) | 7.0 (3.2) | 7.1 (3.3) | 7.7 (3.0) | 0.01 |
|
| |||||
| Pre-operative hematocrit | 35.5 (5.1) | 35.4 (5.2) | 35.8 (5.0) | 35.8 (4.7) | 0.15 |
|
| |||||
| Pre-operative platelet count | 300 (124) | 294 (120) | 308 (128) | 330 (139) | <0.001 |
|
| |||||
| Pre-operative serum sodium | 138.8 (3.0) | 138.8 (3.0) | 138.6 (3.1) | 138.6 (3.4) | 0.39 |
Data presented as (%) for categorical variables, mean (SD) for normally distributed continuous variables, and median (IQR) for nonparametric continuous variables. ASA = American Society of Anesthesiologists; BMI = body mass index; WBC = white blood cells; NGR = no gross residual.
Associations between patient characteristics and postoperative complication are described in Table 2. Preoperative albumin was lower among patients who experienced major, minor and any complication (3.7 versus 3.8, all p<0.02). Preoperative WBC was higher among patients who experienced major (7.9 versus 6.8), minor (7.8 versus 6.9) and any complication (7.7 versus 6.8, all p<0.001). This was also the case for preoperative platelet count (290–294 versus 324–328, all p<0.001).
Table 2:
Associations between patient characteristics and postoperative complications
| No postoperative major complication N = 1,771 (78.8) |
Postoperative major complication N = 477 (21.2) |
p-value | No postoperative minor complication N = 1,817 (80.8) |
Postoperative minor complication N = 431 (19.2) |
p-value | No complication N = 1,586 (70.6) |
Any complication N = 662 (29.4) |
p-value | |
|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||
| Age (years) | 0.05 | 0.22 | 0.14 | ||||||
| 18–29 | 13 (0.7) | 11 (2.3) | 19 (1.1) | 5 (1.2) | 12 (0.8) | 12 (1.8) | |||
| 30–39 | 31 (1.8) | 13 (2.7) | 33 (1.8) | 11 (2.6) | 27 (1.7) | 17 (2.6) | |||
| 40–49 | 174 (9.8) | 49 (10.3) | 189 (10.4) | 34 (7.9) | 159 (10.0) | 64 (9.7) | |||
| 50–59 | 437 (24.7) | 105 (22.0) | 443 (24.4) | 99 (23.0) | 393 (24.8) | 149 (22.5) | |||
| 60–69 | 604 (34.1) | 162 (34.0) | 618 (34.0) | 148 (34.3) | 541 (34.1) | 225 (34.0) | |||
| 70–79 | 416 (23.5) | 105 (22.0) | 415 (22.8) | 106 (24.6) | 370 (23.3) | 151 (22.8) | |||
| 80+ | 93 (5.3) | 30 (6.3) | 98 (5.4) | 25 (5.8) | 82 (5.2) | 41 (6.2) | |||
| Unknown | 3 (0.2) | 2 (0.4) | 2 (0.1) | 3 (0.7) | 2 (0.1) | 3 (0.5) | |||
|
| |||||||||
| BMI (kg/m2) | <0.001 | 0.38 | 0.03 | ||||||
| <18.5 | 17 (1.0) | 10 (2.1) | 23 (1.3) | 4 (0.9) | 17 (1.1) | 10 (1.5) | |||
| 18.5–24.9 | 555 (31.3) | 113 (23.7) | 553 (30.4) | 115 (26.7) | 493 (31.1) | 175 (26.4) | |||
| 25–29.9 | 571 (32.2) | 136 (28.5) | 573 (31.5) | 134 (31.1) | 514 (32.4) | 193 (29.2) | |||
| 30–34.9 | 338 (19.1) | 111 (23.3) | 362 (19.9) | 87 (20.2) | 307 (19.4) | 142 (21.5) | |||
| 35–39.9 | 159 (9.0) | 57 (12.0) | 162 (8.9) | 54 (12.5) | 137 (8.6) | 79 (11.9) | |||
| 40–49.9 | 91 (5.1) | 32 (6.7) | 96 (5.3) | 27 (6.3) | 82 (5.2) | 41 (6.2) | |||
| 50–100 | 9 (0.5) | 8 (1.7) | 14 (0.8) | 3 (0.7) | 9 (0.6) | 8 (1.2) | |||
| Unknown | 31 (1.8) | 10 (2.1) | 34 (1.9) | 7 (1.6) | 27 (1.7) | 14 (2.1) | |||
|
| |||||||||
| >10% weight loss in preceding 6 months | 114 (6.4) | 39 (8.2) | 0.18 | 122 (6.7) | 31 (7.2) | 0.72 | 99 (6.2) | 54 (8.2) | 0.1 |
|
| |||||||||
| Race | 0.60 | 0.83 | 0.64 | ||||||
| White | 1,256 (70.9) | 339 (71.1) | 1,288 (70.9) | 307 (71.2) | 1,127 (71.1) | 468 (70.7) | |||
| Black | 87 (4.9) | 27 (5.7) | 89 (4.9) | 25 (5.8) | 76 (4.8) | 38 (5.7) | |||
| Asian | 65 (3.7) | 12 (2.5) | 62 (3.4) | 15 (3.5) | 58 (3.7) | 19 (2.9) | |||
| Unknown | 363 (20.5) | 99 (20.6) | 378 (20.8) | 84 (19.5) | 325 (20.5) | 137 (20.7) | |||
|
| |||||||||
| Hispanic | 0.21 | 0.49 | 0.23 | ||||||
| Yes | 79 (4.5) | 13 (2.7) | 78 (4.3) | 14 (3.3) | 72 (4.5) | 20 (3.0) | |||
| No | 1,368 (77.2) | 380 (79.7) | 1,405 (77.3) | 343 (79.6) | 1,224 (77.2) | 524 (79.2) | |||
| Unknown | 324 (18.2) | 84 (17.6) | 334 (18.4) | 74 (17.2) | 290 (18.3) | 118 (17.8) | |||
|
| |||||||||
| Hypertension | 672 (37.9) | 203 (42.6) | 0.07 | 697 (38.4) | 178 (41.3) | 0.26 | 600 (37.8) | 275 (41.5) | 0.1 |
|
| |||||||||
| Smoking | 192 (10.8) | 65 (13.6) | 0.09 | 204 (11.2) | 53 (12.3) | 0.53 | 173 (10.9) | 84 (12.7) | 0.23 |
|
| |||||||||
| Diabetes | 177 (10.0) | 52 (10.9) | 0.56 | 182 (10.0) | 47 (10.9) | 0.58 | 154 (9.7) | 75 (11.3) | 0.25 |
|
| |||||||||
| Congestive health failure in preceding 30 days | 1 (0.1) | 1 (0.2) | 0.32 | 2 (0.1) | 0 (0.0) | 0.49 | 1 (0.1) | 1 (0.2) | 0.52 |
|
| |||||||||
| ASA score | 0.07 | 0.12 | 0.01 | ||||||
| 1 | 32 (1.8) | 4 (0.8) | 33 (1.8) | 3 (0.7) | 31 (2.0) | 5 (0.8) | |||
| 2 | 547 (30.9) | 144 (30.2) | 571 (31.4) | 120 (27.8) | 494 (31.2) | 197 (29.8) | |||
| 3 | 1,083 (61.2) | 284 (59.5) | 1,096 (60.3) | 271 (62.9) | 968 (61.0) | 399 (60.3) | |||
| 4+ | 108 (6.1) | 45 (9.4) | 116 (6.4) | 37 (8.6) | 92 (5.8) | 61 (9.2) | |||
| Unknown | 1 (0.1) | 0 (0.0) | 1 (0.1) | 0 (0.0) | 1 (0.1) | 0 (0.0) | |||
|
| |||||||||
| Prior abdominal surgery | 475 (26.8) | 137 (28.7) | 0.41 | 491 (27.0) | 121 (28.1) | 0.66 | 417 (26.3) | 195 (29.5) | 0.13 |
|
| |||||||||
| Prior pelvic surgery | 890 (50.3) | 220 (46.1) | 0.11 | 905 (49.8) | 205 (47.6) | 0.4 | 800 (50.4) | 310 (46.8) | 0.12 |
|
| |||||||||
| Parity | 0.4 | 0.9 | 0.35 | ||||||
| 0 | 444 (25.1) | 138 (28.9) | 469 (25.8) | 113 (26.2) | 396 (25.0) | 186 (28.1) | |||
| 1 | 288 (16.3) | 72 (15.1) | 288 (15.9) | 72 (16.7) | 254 (16.0) | 106 (16.0) | |||
| 2 | 553 (31.2) | 142 (29.8) | 568 (31.3) | 127 (29.5) | 505 (31.8) | 190 (28.7) | |||
| 3+ | 486 (27.4) | 125 (26.2) | 492 (27.1) | 119 (27.6) | 431 (27.2) | 180 (27.2) | |||
|
| |||||||||
| Stage | 0.01 | 0.002 | <0.001 | ||||||
| IIIB | 271 (15.3) | 55 (11.5) | 286 (15.7) | 40 (9.3) | 257 (16.2) | 69 (10.4) | |||
| IIIC | 1,170 (66.1) | 350 (73.4) | 1,206 (66.4) | 314 (72.9) | 1,036 (65.3) | 484 (73.1) | |||
| IV | 330 (18.6) | 72 (15.1) | 325 (17.9) | 77 (17.9) | 293 (18.5) | 109 (16.5) | |||
|
| |||||||||
| Year of operation | 0.02 | 0.05 | 0.007 | ||||||
| 2014 | 182 (10.3) | 67 (14.1) | 192 (10.6) | 57 (13.2) | 164 (10.3) | 85 (12.8) | |||
| 2015 | 206 (11.6) | 72 (15.1) | 214 (11.8) | 64 (14.9) | 177 (11.2) | 101 (15.3) | |||
| 2016 | 288 (16.3) | 80 (16.8) | 290 (16.0) | 78 (18.1) | 253 (15.6) | 115 (17.4) | |||
| 2017 | 365 (20.6) | 85 (17.8) | 364 (20.0) | 86 (20.0) | 324 (20.4) | 126 (19.0) | |||
| 2018 | 340 (19.2) | 88 (18.5) | 357 (20.0) | 71 (16.5) | 310 (19.6) | 118 (17.8) | |||
| 2019 | 390 (22.0) | 85 (17.8) | 400 (22.0) | 75 (17.4) | 358 (22.6) | 117 (17.7) | |||
|
| |||||||||
| Preoperative albumin | 3.8 (0.5) | 3.7 (0.6) | 0.004 | 3.8 (0.5) | 3.7 (0.6) | 0.02 | 3.8 (0.5) | 3.7 (0.6) | <0.001 |
|
| |||||||||
| Preoperative creatinine | 0.77 (0.21) | 0.84 (0.62) | <0.001 | 0.78 (0.32) | 0.81 (0.42) | 0.09 | 0.77 (0.21) | 0.82 (0.54) | <0.001 |
|
| |||||||||
| Preoperative WBC | 6.8 (3.0) | 7.9 (3.8) | <0.001 | 6.9 (3.0) | 7.8 (3.9) | <0.001 | 6.8 (3.0) | 7.7 (3.7) | <0.001 |
|
| |||||||||
| Preoperative hematocrit | 35.5 (5.1) | 35.5 (5.2) | 0.9 | 35.5 (5.1) | 35.4 (5.2) | 0.75 | 35.5 (5.1) | 35.5 (5.2) | 0.8 |
|
| |||||||||
| Preoperative platelet count | 294 (121) | 324 (132) | <0.001 | 294 (121) | 328 (131) | <0.001 | 290 (119) | 324 (132) | <0.001 |
|
| |||||||||
| Preoperative sodium | 138.8 (2.9) | 138.5 (3.4) | 0.07 | 138.9 (2.9) | 138.3 (3.4) | 0.006 | 138.9 (2.8) | 138.4 (3.4) | 0.002 |
Data presented as (%) for categorical variables, mean (SD) for normally distributed continuous variables, and median (IQR) for nonparametric continuous variables. ASA = American Society of Anesthesiologists; BMI = body mass index; WBC = white blood cells.
Associations between preoperative disease location and extent of residual disease are described in Table 3. Patients who had a NGR resection were significantly less likely to have disease involving the bowel mesentery, bowel serosa, liver, diaphragm, and pelvis at the time of abdominal entry, compared with patients who underwent suboptimal or optimal resection (all p<0.001). Considering patients with residual disease at the conclusion of surgery, those with a suboptimal result were more likely to have residual disease involving the bowel serosa, liver and spleen compared with patients who underwent optimal resection (38.4%, 16.0% and 7.3% versus 28.0%, 6.8% and 2.6% all p<0.01). Patients who underwent optimal and suboptimal resections were equally likely to have residual disease involving the bowel mesentery, diaphragm and pelvis.
Table 3:
Association between disease location and extent of residual disease
| Overall N = 2,248 |
NGR N = 1,538 (68.4) |
Optimal N = 504 (22.4) |
Suboptimal N = 206 (9.2) |
p-value | |
|---|---|---|---|---|---|
|
| |||||
| Preoperative Tumor Burden: | |||||
| Bowel serosa | 1,058 (47.1) | 655 (42.6) | 281 (55.8) | 122 (59.2) | <0.001 |
| Bowel mesentery | 1,914 (85.1) | 1,271 (82.6) | 460 (91.3) | 183 (88.8) | <0.001 |
| Liver | 311 (13.8) | 185 (12.0) | 84 (16.7) | 42 (20.4) | <0.001 |
| Spleen | 207 (9.2) | 119 (7.7) | 62 (12.3) | 26 (12.6) | 0.002 |
| Diaphragm | 828 (36.8) | 428 (27.8) | 290 (57.5) | 110 (53.4) | <0.001 |
| Pelvis | 1,602 (71.3) | 1,029 (66.9) | 415 (82.3) | 158 (76.7) | <0.001 |
|
| |||||
| Residual Disease: | N = 710 | ||||
| Bowel serosa | 220 (31.0) | 141 (28.0) | 79 (38.4) | 0.007 | |
| Bowel mesentery | 336 (47.3) | 227 (45.0) | 109 (52.9) | 0.06 | |
| Liver | 67 (9.4) | 34 (6.8) | 33 (16.0) | <0.001 | |
| Spleen | 28 (3.9) | 13 (2.6) | 15 (7.3) | 0.003 | |
| Diaphragm | 285 (40.1) | 201 (39.9) | 84 (40.8) | 0.83 | |
| Pelvis | 300 (42.3) | 209 (41.5) | 91 (44.2) | 0.51 | |
Data presented as (%) for categorical variables. NGR = no gross residual.
For the primary outcome, there were significant differences by extent of resection (Table 4). Optimal cytoreduction patients had the highest rates of any complication (35.5%) compared with those who underwent resection to NGR disease (27.0%) and suboptimal cytoreduction (33.0%, p<0.001). Patients who underwent optimal resection also had the longest operating room times and procedures that were most surgically complex (203 min, 43.6 RVU) compared with patients who underwent resection to NGR disease (196 min, 41.9 RVU) and suboptimal resection (187 min, 37.1 RVU, both p<0.05). Surgical efficiency did not differ based on extent of resection. Additionally, patients who underwent optimal resection had the highest rates of minor complications (24.0%) compared to NGR (17.2%) and suboptimal (21.8%) resection patients (p=0.002). However, major complication rates were not significantly different (24.2% versus 19.9% and 23.8%, p=0.08). Length of stay was increased for patients who underwent optimal (5 days, IQR 4–8) and suboptimal resection (6 days, IQR 4–8), compared with patients who underwent NGR cytoreduction (5 days, IQR 3–7, p<0.001).
Table 4:
Associations between operative characteristics and extent of residual disease
| Overall N = 2,248 (100) |
NGR N = 1,538 (68.4) |
Optimal N = 504 (22.4) |
Suboptimal N = 206 (9.2) |
p-value | |
|---|---|---|---|---|---|
| Median operative time (min) | 197 (144–269) | 196 (144–269) | 203 (150–280) | 187 (126–248) | 0.01 |
| Total RVUs | 41.2 (34.1–64.2) | 41.9 (34.1–64.9) | 43.6 (34.1–64.9) | 37.1 (34.1–57.9) | 0.04 |
| Surgical efficiency (RVU/hour) | 14.1 (10.3–19.1) | 14.3 (10.3–18.9) | 13.6 (10.2–19.4) | 13.7 (10.3–19.8) | 0.98 |
| Any complication | 662 (29.4) | 415 (27.0) | 179 (35.5) | 68 (33.0) | <0.001 |
| Minor complication | 431 (19.2) | 265 (17.2) | 121 (24.0) | 45 (21.8) | 0.002 |
| Major complication | 477 (21.2) | 306 (19.9) | 122 (24.2) | 49 (23.8) | 0.08 |
| Length of stay (days) | 5 (3–7) | 5 (3–7) | 5 (4–8) | 6 (4–8) | <0.001 |
Data presented as (%) for categorical variables, mean (SD) for normally distributed continuous variables, and median (IQR) for nonparametric continuous variables. NGR = no gross residual; RVUs = relative value units.
We constructed a multivariable logistic regression model to determine the association between cytoreductive surgery outcome and postoperative complication (Table 5). Patients who underwent optimal resection had increased odds of experiencing any (OR 1.49, 95%CI 1.20–1.85) and minor complications (OR 1.52, 95%CI 1.19–1.94) compared to those who underwent resection to NGR disease. Given the differences in clinical characteristics between patient groups, we adjusted for stage, race, Hispanic ethnicity, operative year, ASA score, BMI, weight loss and preoperative laboratory values. After adjustment, optimal resection patients continued to demonstrate the highest odds of experiencing any (aOR 1.43, 95%CI 1.12–1.83) and minor complications (aOR 1.44, 95%CI 1.09–1.91). For patients who underwent optimal resection, odds of experiencing a major complication appeared greater compared to patients who underwent NGR resection (OR 1.29, 95%CI 1.01–1.63). However, this association was not significant after adjustment (aOR 1.20, 95%CI 0.91–1.58). Odds of experiencing any complication, minor complications, and major complications were not different between NGR and suboptimal resection patients with and without adjustment.
Table 5:
Association of postoperative complications with extent of residual disease
| OR | 95% Cl | aOR | 95% Cl | |
|---|---|---|---|---|
| Odds of Any Complication | ||||
| NGR | Referent | |||
| Optimal | 1.49 | 1.20–1.85 | 1.43 | 1.12–1.83 |
| Suboptimal | 1.33 | 0.98–1.82 | 1.21 | 0.84–1.75 |
| Odds of Minor Complication | ||||
| NGR | Referent | |||
| Optimal | 1.52 | 1.19–1.94 | 1.44 | 1.09–1.91 |
| Suboptimal | 1.34 | 0.94–1.92 | 1.14 | 0.74–1.74 |
| Odds of Major Complication | ||||
| NGR | Referent | |||
| Optimal | 1.29 | 1.01–1.63 | 1.2 | 0.91–1.58 |
| Suboptimal | 1.26 | 0.89–1.77 | 1.2 | 0.80–1.79 |
Adjusted odds ratios are adjusted for operative year, stage, race, Hispanic ethnicity, American society of anesthesiologists score, body mass index, preoperative laboratory values, and weight loss. NGR = no gross residual.
DISCUSSION
In this study, we found that optimal resection at the time of debulking surgery for ovarian cancer was associated with an increase in 30-day postoperative complications compared with resection to NGR disease and suboptimal resection. Optimal cytoreduction patients had the highest rates of major, minor and any complication. Patients who underwent optimal resection also had the longest operating room times and procedures that were most surgically complex. Patients who underwent optimal resection had increased odds of experiencing any complication and minor complications but did not have significantly increased odds of a major complication, compared with patients who underwent NGR disease resection, after adjustment.
Postoperative complications are influenced by surgical factors like extent of resection as well as by patient factors such as age, performance status and medical comorbidities.17 In our cohort, patients who experienced complications were more likely to be obese and had higher ASA scores. Lower preoperative albumin and serum sodium levels were associated with complications, as were higher preoperative WBC, platelet count and creatinine. Between 2014 and 2019, the proportion of patients who experienced postoperative complications decreased. This change likely reflects increased uptake of neoadjuvant chemotherapy (NACT) in the United States, which nearly all series suggest decreases the morbidity of cytoreductive surgery as well as an increased focus by institutions on surgical quality and minimizing postoperative complications.11,18 Extent of resection achieved by surgeons was also influenced by various patient factors. Patients who had complete cytoreduction to NGR disease were less likely to have lost >10% of their body weight in the six months preceding surgery. These patients were more likely to be White or Asian, less likely to be Hispanic, and more likely to have stage IIIB disease. Patients who underwent NGR resection also had lower preoperative WBC and platelet counts compared with patients who had an optimal or suboptimal resection of disease. Population-based data suggest that elderly women who undergo radical cytoreduction experience a 2–4x higher post-operative complication rate11. Interestingly, the association of age with postoperative complication was not born out in our data. It may be that frailty, rather than age, is more closely correlated with adverse surgical outcomes among contemporary patients with advanced ovarian cancer.
The percentage of patients who undergo optimal cytoreduction for advanced disease varies widely in the literature from 15%–85%.19 This is consistent with our results with 22.4% of patients undergoing optimal cytoreduction and an additional 68.4% undergoing resection to NGR. The rate of major complications observed in these patients (21.2%) is also consistent with prior literature reporting 18%–22% major complications in similar patients who underwent cytoreductive surgery.10,20 Patients who underwent optimal cytoreduction had the longest operative times (203 mins) and the highest rates of postoperative complications (35.5%). This is consistent with existing literature which finds an association between operative time and increased risk of postoperative complications.20,21 Our study reports an overall complication rate of 29.4%, which is similar to the 33% overall complication rate reported by a group in the Netherlands that classified 30 day postoperative complications according to NSQIP definitions.21
The relationship between disease burden and surgical complexity is intuitive; more surgery will be needed to remove more widespread disease. However, in this study, we found a difference between the surgical effort for NGR and optimal resections; optimal cytoreductions took longer to perform and incurred higher RVUs, a reflection of the technical complexity of the procedures performed at the time of surgery. Radical cytoreductive surgeries are associated with predictable increases in morbidity and mortality for ovarian cancer patients.17,21,22 When the result of these complex procedures is NGR, postoperative complications may be more acceptable to patients and surgeons than when the outcome is optimal cytoreduction. Despite the morbidity of radical cytoreductive surgery, most gynecologic oncologists feel that the acute debility is offset by long-term oncologic benefits and this study is not designed to examine these long term, and important, outcomes.23 However, a need exists to better define the likelihood of successful surgical effort to NGR disease either preoperatively or at the time of abdominal entry to prevent not only poor long-term oncologic outcomes, but short-term postoperative complications as well.
Our study makes use of information collected in the ACS NSQIP database and its targeted hysterectomy files between 2014 and 2019. In contrast to prior studies, this national dataset avoids the weaknesses of single-geographic area, single-institution and single-surgeon studies which may not be generalizable, as surgical-decision making, skill, and reporting of outcomes may vary from center to center and surgeon to surgeon and are notoriously hard to measure. Conversely, although many institutions participate in NSQIP, participation is voluntary and academic and large institutions are over-represented. In this study, we found several cases of optimal and suboptimal cytoreduction attributed to residual disease on the diaphragm, spleen, and pelvis. This information is important to consider as these are not accepted locations to leave disease in the current paradigm, but may be more likely in certain populations or circumstances (e.g. miliary disease on the rectosigmoid colon, frail patient) and these data suggest this is happening to some degree nationally. We are also limited by our inability to describe the percentage of patients in this cohort who received NACT, although outcome of surgery in terms of residual disease is an important prognostic factor for patients undergoing both primary and interval debulking surgery. In contrast to other databases that utilize billing and coding data only, NSQIP data is prospectively collected by trained personnel with the express purpose of improving surgical quality. Periodic audits are performed and reveal only a 1.8% disagreement rate, confirming accuracy of the data.12 NSQIP records 30-day postoperative data and thus our complication rates do not include events that occurred after that time point and may underestimate true rates.
CONCLUSION
We found that in a large surgical quality improvement database, among patients with advanced ovarian cancer who underwent debulking surgery, optimal cytoreduction was associated with more postoperative complications compared with NGR disease resection and suboptimal cytoreduction. Our data shed light on current national practice patterns and elucidate some of the relationships in the complex interplay between surgical effort, residual disease, and complication.
Synopsis:
Women with advanced ovarian cancer who undergo optimal cytoreduction endure complex surgeries that require significant operating room time and frequently experience postoperative complications.
Acknowledgements:
Dr. Barber is supported by career development funds from the NIA (P30AG059988-01A1) and the GOG Foundation.
Footnotes
Conflicts of interest: The authors declare no potential conflicts of interest.
NSQIP disclosure: American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) and the hospitals participating are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors.
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