Abstract
Purpose:
Robot-assisted surgery has been touted as offering superior outcomes in various oncologic surgeries. We sought to evaluate the comparative effectiveness of robotic radical nephrectomy (RRN) compared with laparoscopic radical nephrectomy (LRN) in regard to hospital charges, complications, and survival.
Materials and Methods:
Using the Surveillance Epidemiology and End Results (SEER) Program-Medicare linked database, we identified patients over the age of 65 who underwent radical nephrectomy (
Results:
Two hundred forty-one patients underwent RRN, and 574 patients underwent LRN. After propensity score matching, the adverse events rate and length of stay were similar between two groups (Major Events: 5.7% vs 6.1%, p = 0.84; prolonged LOS: 17.8% vs 16.1%, p = 0.62). The inpatient charges following RRN were significantly higher than those of LRN ($53,681 vs $44,161, p < 0.01). The mean follow-up of the cohort was 3.2 years. Estimated overall survival (88.0% vs 87.9%, p = 0.90) and cancer-specific survival (98.1% vs 96.4%, p = 0.25) were similar between the two matched cohorts at 3 years.
Conclusion:
The robotic platform showed no benefit over standard laparoscopy for
Introduction
R
The first robotic radical nephrectomy (RRN) for renal-cell carcinoma (RCC) was described by Klingler at al. in 2005. 5 Since its introduction, multiple case series have demonstrated that RRN is both a safe and effective approach to renal extirpative surgery. 6 Exclusion criteria for RRN and LRN are no different, and both are considered suitable options for surgical management of renal tumors. 7
LRN and RRN are often combined to report on generalizations about minimally invasive surgery (MIS). Nevertheless, from a technical standpoint there are distinct differences between the approaches, with clinical, oncologic, and cost implications. Pure laparoscopic surgery is thought to have a steeper learning curve than a robotic platform, as laparoscopic surgery has limited maneuverability. 8 Robotic surgery offers potential advantages in surgical dexterity and intraoperative imaging, which may facilitate hilar dissection and control of the kidney vessels. 7
Although the robotic approach to RN is increasing, 9 little data to support this increased adaptation exist, especially comparing the two surgical approaches in regard to perioperative and oncologic outcomes. We sought to compare LRN vs RRN in regard to cost, complications, and survival.
Methods
Data source
This study was based on the US National Cancer Institute Surveillance Epidemiology and End Results (SEER) Program and Medicare insurance program linked database. SEER is a nationally representative population-based cancer registry that collects incidence treatment and mortality data. 10 Effective linkage with Medicare hospital and physician claims is achieved for more than 90% of patients. 11
Study population
We identified patients older than 65 years of age who were found to have kidney cancer between 2001 and 2011 and underwent
Exposure and study outcomes
We identified RN (ICD-9-CM 55.5, 55.51) using International Classification of Disease, 9th revision (ICD-9) procedure code. Patients who underwent bilateral nephrectomy (ICD-9-CM 55.54) were excluded. MIS was determined by concurrent laparoscopic (ICD-9-CM 54.21, 54.51) and robotic procedural codes (ICD-9-CM 17.4, 17.42, 17.49). Only the index procedure for each patient was used for the analyses.
The primary outcome was overall survival and RCC-specific survival. Overall survival was ascertained by occurrence of death from any cause provided in the Medicare and SEER files. Medicare date of death was used when available, otherwise the SEER date of death was used. Duration of survival was defined as the time between index surgery and death or until December 2013. When death did not occur, patients were censored at the end of the study period (December 2013). RCC-specific survival was determined based on cause of deaths indicated in SEER data. Patients were further censored at the time of death when they had non-RCC-related death.
Our secondary outcome was in-hospital outcomes, including major adverse events (death, acute myocardial infarction, pulmonary embolism, sepsis, and shock), procedural complications (iatrogenic complications, infection, and wound complications), respiratory complications, acute kidney injury (AKI), intensive care unit (ICU) use, length of stay (LOS), and total inpatient charges. Prolonged LOS was defined as above the 75th percentile (>5 days). 13
Patient covariates
For each patient, demographics (age, sex, race and ethnicity, marital status, income, and education tertiles), cancer characteristics (histology, tumor grade, tumor size, and T stage), and comorbidities were extracted from SEER and Medicare files. Age was defined as age at the time of procedure. Socioeconomic characteristics were obtained through the 2000 census at the census tract level. Comorbidities were collected within 12 months before index surgery date from Medicare inpatient discharges, carrier files, outpatient records, and Home Health Agency records using algorithms validated by Elixhauser. 14 Major comorbidities comprised coronary artery disease, hypertension, congestive heart failure, diabetes, chronic pulmonary disease, obesity, anemia, peripheral vascular disease, cerebrovascular disease, hypercalcemia, and chronic kidney disease.
Statistical analyses
For patients who underwent LRN and RRN, events and percentages were presented for baseline patient demographics, cancer variables, and comorbidities. Baseline characteristics were compared between the RRN and LRN patient groups. Propensity score matching was used to adjust for differences in baseline characteristics between RRN and LRN patients. 15 Multivariable logistic regression based on patient characteristics, procedure year, cancer variables, and comorbidities was performed to obtain propensity scores for each individual. A missing category was created for marital status, tumor grade, and tumor size before matching. Then, 1:1 fixed ratio nearest neighbor matching of the two groups was performed, using a caliper width of 0.2 of the pooled standard deviation of the logit of the propensity score. We assessed for balance in matching by assessing differences in baseline variables between groups before and after propensity score matching (Appendix Table 1).
In-hospital outcomes were examined before and after propensity score matching. Median LOS and inpatient charges were obtained. Differences between groups were assessed using χ 2 tests and Wilcoxon rank sum tests in the entire cohort and using stratified Mantel–Haenszel χ 2 tests and signed rank tests for paired data in the matched cohort for binary and continuous variables, respectively. Risk ratio and its 95% confidence interval were calculated for in-hospital complications, ICU use, and prolonged LOS.
Time-to-event analyses were conducted in cohorts before and after matching to compare overall and RCC-specific survival between groups. Kaplan–Meier curves were constructed and visually inspected. Estimated overall survivals and estimated RCC-specific survival with 95% CI at 3 years were obtained using Kaplan–Meier analysis, and differences in survival between the two groups were compared using the log-rank test in the cohort before matching and using the Prentice–Wilcoxon test in cohorts after matching. All analyses were performed using SAS v9.3 (SAS Institute Inc., Cary, NC).
Results
Patient characteristics
From October 2008 to the end of the study period, 574 kidney cancer patients underwent LRN and 241 patients underwent RRN. In the unmatched cohort, patients who underwent robotic surgery were more likely to be nonwhite (19.9% vs 11.8%, p = 0.01), live in metropolitan areas (Metro: 90.9% vs 85.9%, p = 0.05), and have lower indicators of socioeconomic status (i.e., Low Education: 40.7% vs 28.6%, p < 0.01) compared with patients undergoing laparoscopic surgery (Table 1). In addition, robotic surgery tended to be performed among patients with smaller tumors (average 4.8 vs 5.5 cm, p < 0.01). Baseline characteristics were balanced between the two groups after propensity score matching.
In-hospital outcomes and charges
Overall, after propensity score matching, in-hospital outcomes, including risks of major events (5.7% vs 6.1%, p = 0.84), procedural complications (p = 0.80), respiratory complications (9.1% vs 6.5%, p = 0.30), AKI (8.7% vs 10.9%, p = 0.43), and ICU use, (18.7% vs 20.0%, p = 0.72) were similar between the two groups (Table 2). Patients undergoing RRN and LRN also had similar LOS (prolonged LOS: 17.8% vs 16.1%, p = 0.62). However, inpatient charges were significantly higher for RRN when compared with LRN (median: $53,681 vs $44,161, p < 0.01).
Major events included inpatient death, acute myocardial infarction, pulmonary embolism, sepsis, and shock.
Procedural complications included infection and iatrogenic and wound complications.
AKI = acute kidney injury; ICU = intensive care unit; IQR = interquartile range; NR = not reportable for events <11; RR = risk ratio.
Intermediate-term survival
During a mean follow-up of 3.2 years, 101 patients undergoing LRN and 31 patients undergoing RRN died from any cause. More specifically, 24 patients in the LRN and <10 patients in the RRN group died from kidney cancer during follow-up. Before propensity score matching, the estimated overall survival at 3 years was 88.0% (95% CI 82.5%, 91.8%) in RRN and 83.7% (95% CI 80.3%, 86.6%) in LRN groups. The estimated RCC-specific survival at 3 years was 97.8% (95% CI 94.8%, 99.1%) and 95.7% (95% CI 93.6%, 97.1%) in the RRN and LRN groups, respectively. After propensity score matching, the estimated overall survival was 88.0% (82.5%–91.9%) for RRN compared with 87.9% (82.5%–91.7%) in the LRN group. The estimated RCC-specific survival was 98.1% (95% CI 95.1%, 99.3%) vs 96.4% (95% CI 92.9%, 98.2%) in RRN vs LRN patients, respectively (Table 3). Generally, overall survival (Prentice–Wilcoxon test: p = 0.90) and RCC-specific survival (Prentice–Wilcoxon test: p = 0.25) were similar between the two groups in the matched cohort (Fig 1).

Kaplan–Meier estimates with number of subjects at risk and 95% Hall–Wellner Bands for overall and cancer-specific survival among Medicare beneficiaries undergoing robotic vs laparoscopic radical nephrectomy.
Discussion
RRN is considered a safe procedure and a suitable option for patients who require surgical removal of the entire renal unit. 5 However, the utility of the robotic platform in the setting of RN has been questioned largely due to concerns such as cost and increased time and effort associated with robotic docking. 16 Nevertheless, it has been difficult to conclude if further advantages offered from robotic technology exist, as data on direct comparison of RRN to LRN are few and often consist of small cohorts with limited follow-up. 17 In the current population-based contemporary study, we found no difference in survival or adverse event rates between patients undergoing RRN or LRN, although cost estimates were significantly higher with RRN. These results contribute to the limited but growing data that fail to demonstrate a surgical or economic benefit to use of a robotic platform in the RN setting.
We found no difference in cancer-specific or overall survival between RRN and LRN with intermediate-term mean follow-up of 3.2 years. These results contribute to prior studies that have demonstrated short-term oncologic efficacy of minimally invasive RN. A recent systematic review by Asimakopoulos and colleagues 7 included 10 studies evaluating the oncologic efficacy of RRN for clinically localized and/or advanced cases of RCC. Of those, only one study in 2009 by Hemal and Kumar 17 directly compared the efficacy of RRN to LRN. In comparing 15 patients who underwent RRN with 15 patients who underwent LRN for cT1-T2 RCC, authors found no difference in local, port-site, or distal recurrence rates after a mean follow-up of 8.3 and 9.1 months, respectively. Proper use of robotic arms can reduce the complexity of laparoscopic tasks being performed by the bedside assistant and, therefore, maximize console surgeon independence. 18 While it stands to reason that this could lead to different outcomes between the two approaches, our results do not support this theory.
We found no difference in major in-hospital events, procedural complications, or LOS between the two approaches. Potential advantages of the robotic approach over laparoscopic have been suggested, which may provide better perioperative outcomes for RRN. For instance, the use of an articulated clip applier allows for the surgeon to approach the kidney vessels at angles not achievable with a conventional laparoscopic clip applier, and EndoWrist technology may allow for easier ligation of the kidney vessels. However, we saw no difference in major events between groups, including death, ICU use, and blood transfusion. Our results at the population-level complement single-center or single-surgeon studies reporting no significant difference in measured perioperative outcomes. 19,20
Total inpatient charges were significantly higher when surgery was performed by a robotic approach. Our results are consistent with multiple reports that have shown robotic surgery to be equal to or more expensive than laparoscopic surgery. 21 Using the Nationwide Inpatient Sample database, Yang and colleagues 22 found median total charges were higher for RRN vs LRN ($47,036 vs $38,068, p < 0.001), finding total charges and hospital costs of RRN were around $9000 and $3500 more than LRN, respectively. A single institution study by Boger and colleagues 20 concluded that robotic assistance adds about $1300 in direct costs to surgery compared with a laparoscopic approach and nearly $400 more in disposable costs per patient. In a prospective comparison, Hemal and Kumar 17 reported RRN added a mean of 46 minutes of operative time compared with LRN. Although they did not directly analyze for cost, others have suggested time-based operating room costs are around $54/minute for the first 30 minutes and $11/minute thereafter. 20 In the setting of partial nephrectomy, Alemozaffar and colleagues 23 reported no difference in variable costs between robotic-assisted and laparoscopic approaches, and Yu and colleagues 24 reported no difference in costs among open, laparoscopic, and robotic partial nephrectomy. This suggests that the need for reconstruction (i.e., partial nephrectomy) may be the difference in a procedure being cost neutral or cost negative. 22 However, when removing the entire renal unit, our estimates are consistent with previous reports of significantly higher costs incurred when utilizing a robotic platform.
Finally, we identified several sociodemographic and tumor characteristics associated with the surgical approach. Higher utilization of RRN over LRN was seen in those who live in metropolitan areas, consistent with reports that patients undergoing total nephrectomy at hospitals in moderately or highly competitive markers are more likely to undergo robotic-assisted surgery. 25 In addition, we noted some baseline differences in patient characteristics between surgical approaches, including race and education level. Racial, gender, and socioeconomic status have been previously investigated in the setting of RCC. In small renal masses, black patients are more likely to undergo nonsurgical management and less likely to undergo partial nephrectomy than RN if operated on. 26 Similarly, men are more likely than women to be nonsurgically managed, but more likely to receive a partial nephrectomy. Risk aversion, access to care, and acceptability of novel cancer treatments have all been implicated in treatment disparities. Furthermore, marketing for robotic surgery is increasingly web based, often promoting improved outcomes without describing a comparison group or making reference to evidence-based data to support claims. 27 Thus, it is possible that susceptibility to marketing may factor into patient decision-making, as inequalities in communication, leading to differences among social groups to access, seek, process, and use information in direct to consumer advertising, are well documented. 28 However, it is also possible that sociodemographic differences in our study are reflective of unidentified confounders, as by utilizing an administrative data set designed for billing purposes, we fail to capture individual patient and physician preferences that impact operative decision-making. Regardless, as we found no difference in perioperative or survival outcomes between surgical approaches, it is unlikely these differences led to any significant treatment disparities.
This study possesses several strengths. Through utilization of two large population databases (SEER-Medicare), we provide a comprehensive representation of patient outcomes across the United States. In doing so, we provide population-based evidence that with intermediate-term follow-up, no difference in overall or cancer-specific survival exists between minimally invasive surgical approaches to RN. These results have not been previously reported on this scale, and we believe they have important significance to the patient, surgeon, and medical community. That said, our study does have limitations, as we were unable to capture patients who underwent minimally invasive RN before 2008, when robotic codes became effective. While this limits our sample size, it frames our study in a contemporary, relevant setting.
Second, as Medicare provides healthcare benefits to Americans ≥65 years old, our results may have limited generalizability to younger patients and those treated internationally or in non-SEER regions. Third, while propensity score methods allowed us to adjust for known confounders, neither could we adjust for unobserved differences such as tumor complexity nor were we able to distinguish pure laparoscopic from hand-assisted laparoscopic surgical technique. While some have suggested that RRN may minimize the technical difficulties associated with laparoscopy and permit surgeons to undertake more challenging cases such as complex IVC thrombi, these are currently limited to case reports and modest case series. 29,30 In addition, we were unable to compare measures of postoperative convalescence, such as quality of life metrics or analgesic requirements, as SEER does not capture this information. However, we would not anticipate a difference in these measures between the different minimally invasive approaches. Finally, we do not account for the capital and maintenance costs of robotic equipment, which therefore limits our cost analysis. This study has adhered to all appropriate ethical standards. This study is IRB exempt.
Conclusion
The robotic platform demonstrated no benefit over standard laparoscopy for
Footnotes
Acknowledgments
Padraic O'Malley and David M. Golombos are supported by the Frederick J. and Theresa Dow Wallace Fund of the New York Community Trust and by the Ferdinand C. Valentine Fellowship Award from the New York Academy of Medicine.
Author Disclosure Statement
No competing financial interests exist.
Appendix
| Full cohort | Matched cohort | |||||
|---|---|---|---|---|---|---|
| Laparoscopic (n = 574) | Robotic (n = 241) | Diff | Laparoscopic (n = 230) | Robotic (n = 230) | Diff | |
| Age, mean (SD) | 74.1 (6.5) | 73.6 (5.9) | 0.5 | 74.2 (6.2) | 73.7 (6.0) | 0.5 |
| Male | 328 (57.1%) | 153 (63.5%) | 6.3 | 150 (65.2%) | 143 (62.2%) | 3.0 |
| Race | ||||||
| White | 506 (88.2%) | 193 (80.1%) | 8.1 | 191 (83.0%) | 186 (80.9%) | 2.2 |
| Black | 35 (6.1%) | 25 (10.4%) | 4.3 | 21 (9.1%) | 22 (9.6%) | 0.4 |
| Other | 33 (5.7%) | 23 (9.5%) | 3.8 | 18 (7.8%) | 22 (9.6%) | 1.7 |
| Married | 358 (62.4%) | 142 (58.9%) | 3.4 | 140 (60.9%) | 134 (58.3%) | 2.6 |
| Metropolitan residence | 493 (85.9%) | 219 (90.9%) | 5.0 | 22 (9.6%) | 22 (9.6%) | 0.0 |
| Year of procedure | ||||||
| 08–10 | 410 (71.4%) | 121 (50.2%) | 21.2 | 123 (53.5%) | 120 (52.2%) | 1.3 |
| 11–12 | 164 (28.6%) | 120 (49.8%) | 21.2 | 107 (46.5%) | 110 (47.8%) | 1.3 |
| Income | ||||||
| Low | 178 (31.0%) | 80 (33.2%) | 2.2 | 68 (29.6%) | 78 (33.9%) | 4.3 |
| Medium | 185 (32.2%) | 88 (36.5%) | 4.3 | 88 (38.3%) | 80 (34.8%) | 3.5 |
| High | 209 (36.4%) | 72 (29.9%) | 6.5 | 73 (31.7%) | 71 (30.9%) | 0.9 |
| Education | ||||||
| Low | 164 (28.6%) | 98 (40.7%) | 12.1 | 85 (37.0%) | 91 (39.6%) | 2.6 |
| Medium | 204 (35.5%) | 67 (27.8%) | 7.7 | 59 (25.7%) | 65 (28.3%) | 2.6 |
| High | 204 (35.5%) | 75 (31.1%) | 4.4 | 85 (37.0%) | 73 (31.7%) | 5.2 |
| Histology | ||||||
| Clear cell | 385 (67.1%) | 165 (68.5%) | 1.4 | 153 (66.5%) | 158 (68.7%) | 2.2 |
| Papillary | 51 (8.9%) | 24 (10.0%) | 1.1 | 22 (9.6%) | 21 (9.1%) | 0.4 |
| Other | 39 (6.8%) | 20 (8.3%) | 1.5 | 16 (7.0%) | 19 (8.3%) | 1.3 |
| Unclassified | 99 (17.2%) | 32 (13.3%) | 4.0 | 39 (17.0%) | 32 (13.9%) | 3.0 |
| Tumor grade | ||||||
| Grade I | 50 (8.7%) | 24 (10.0%) | 1.2 | 21 (9.1%) | 22 (9.6%) | 0.4 |
| Grade II | 273 (47.6%) | 110 (45.6%) | 1.9 | 112 (48.7%) | 107 (46.5%) | 2.2 |
| Grade III/IV | 186 (32.4%) | 80 (33.1%) | 0.7 | 73 (31.7%) | 76 (33.0%) | 1.3 |
| Unknown | 65 (11.3%) | 27 (11.2%) | 0.1 | 24 (10.4%) | 25 (10.9%) | 0.4 |
| Tumor size, mean (SD), cm | 5.5 (3.4) | 4.8 (2.6) | 0.7 | 4.8 (2.3) | 4.8 (2.6) | 0.0 |
| Tumor stage | ||||||
| T1 | 376 (65.5%) | 177 (73.4%) | 7.9 | 174 (75.7%) | 168 (73.0%) | 2.6 |
| T2 | 63 (11.0%) | 19 (7.9%) | 3.1 | 17 (7.4%) | 19 (8.3%) | 0.9 |
| T3 | 135 (23.5%) | 45 (18.7%) | 4.8 | 39 (17.0%) | 43 (18.7%) | 1.7 |
| Comorbidities | ||||||
| 0–1 | 78 (13.6%) | 30 (12.4%) | 1.1 | 29 (12.6%) | 29 (12.6%) | 0.0 |
| 2–4 | 295 (51.4%) | 119 (49.4%) | 2.0 | 108 (47.0%) | 114 (49.6%) | 2.6 |
| 5+ | 201 (35.0%) | 92 (38.2%) | 3.2 | 93 (40.4%) | 87 (37.8%) | 2.6 |
