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Keywords:

  • partial nephrectomy;
  • radical nephrectomy;
  • survival advantage;
  • observational data;
  • selection bias

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

BACKGROUND

Partial nephrectomy (PN) and radical nephrectomy (RN) are standard treatments for a small renal mass. Retrospective studies suggest an overall survival (OS) advantage, however a randomized phase 3 trial suggests otherwise. The effects of both surgical modalities on OS were evaluated compared with controls.

METHODS

A matched cohort study was performed using the Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset. Individuals treated with PN or RN for localized renal cell carcinoma (RCC) measuring ≤4 cm were compared with 2 control groups (non–muscle-invasive bladder cancer (BCC) and noncancer controls (NCC). Using a greedy algorithm, RCC groups were matched with controls by demographics and comorbidities. OS for surgical groups and controls were compared. The cause of death was evaluated for cancer groups when differences in OS were noted.

RESULTS

Patients undergoing PN and RN were matched with controls. All cancer groups had >95% 10-year cancer-specific survival (CSS). Median OS was similar between RN (9.05 years) and BCC (8.67 years; P = .067) and NCC (8.77 years; P = .49). Median OS was improved for PN (10.45 years) compared with BCC (8.75 years; P<.001) and NCC controls (8.76 years; P<.001). A multivariate Cox hazards model demonstrated that PN improved OS compared with NCC (hazard ratio, 1.257; P<.001) and BCC (hazard ratio, 1.364; P<.001).

CONCLUSIONS

RN patients had similar OS compared with controls, suggesting that this treatment modality does not compromise survival. Patients undergoing PN had improved OS compared with controls, suggesting possible selection bias. The apparent survival advantage conferred by PN in SEER-Medicare case series is likely the result of selection bias involving unmeasured confounders. Cancer 2013;119:2981—2989. © 2013 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Radical nephrectomy (RN) was initially described a half-century ago and involves the complete removal of the kidney, Gerota's fascia, and the ipsilateral adrenal gland. However, en bloc excision of whole organs has been associated with serious adverse effects. In many fields, properly selected patients have been offered a functional lumpectomy, sparing adjacent normal tissue while providing equivalent cancer outcomes. For the past few decades, RN has been the standard treatment for patients who have a small (≤4 cm) renal mass and 2 functional kidneys. However, after multiple retrospective series demonstrated oncologic equipoise, partial nephrectomy (PN) became an option, allowing for the preservation of normal renal parenchyma.[1-3]

Whereas adverse health-related quality of life outcomes associated with procedures such as radical mastectomy are immediately visible, those associated with renal cell carcinoma (RCC) treatment are more subtle due to the long-term consequences of nephron loss. Although it has long been recognized that rendering a patient anephric has life-altering consequences, RN was not believed to pose significant health consequences in the presence of a normal contralateral kidney. In recent years, important studies have demonstrated a correlation between the extent of chronic kidney disease (CKD) and increased rates of cardiac events, hospitalizations, and infections.[4, 5]

Although data on adverse health outcomes have come largely from patients with medical CKD, they have been considered applicable to surgically induced CKD. Several retrospective series have demonstrated that PN could limit the occurrence of CKD compared with RN.[12, 13] Whether decreasing the incidence of CKD with PN translates into an improvement in overall survival (OS) has been intensely debated. Recently, the results of a randomized phase 3 trial by the European Organization for Research and Treatment of Cancer (EORTC 30904) demonstrated an OS advantage with RN compared with PN.[6] Critics of this trial point out that it was underpowered and had significant crossover between treatments; however, it is the only level 1 evidence addressing this question.

Recently, Tan et al[7] applied an instrumental variable analysis (IVA) to minimize selection bias in the comparison between PN and RN. Using SEER-Medicare data, they found that PN provided superior OS.[7] Other studies by Kowalczyk et al[8] and Huang et al[9] have demonstrated similar improvements in OS for small renal tumors treated with PN. Kim et al[10] recently reported the results of a meta-analysis comparing PN and RN and found that PN was associated not only with improved OS, but also with cancer-specific survival (CSS). As there is no oncologic explanation for this finding, it raises the question of whether this is due to selection bias rather than treatment effect.[10]

Due to an uncertain survival advantage with PN and concerns a direct comparison to RN may be fraught with selection bias, we conducted a SEER-Medicare matched cohort study comparing RCC surgical groups with separate controls.[11] By matching PN and RN with separate cancer and noncancer controls, we evaluated how each procedure affected OS. We hypothesized that if RN worsened OS compared with PN, survival would be worse than controls. Similarly, if improvement in OS observed with PN is due to selection bias, then survival would be improved compared with controls.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Data Set and Patient Cohort

The study cohort was defined using the SEER-Medicare data linkage. This dataset encompasses 17 cancer registries and provides detailed clinical and demographic information on approximately 28% of the US population. Follow-up data are also available for patients in the registries. SEER-Medicare linkage contains claims data from the Centers for Medicare and Medicaid Services to measure health care utilization and has a successful linkage rate of >95%.[12]

We identified individuals aged ≥66 years who were diagnosed with RCC between 1992 and 2007. Because SEER-Medicare claims data are available through 2009, this served as the end of follow-up. Patients with RCC were identified in SEER using International Classification of Diseases for Oncology, 3rd Revision codes (ICD-O-3), similar to previous studies.[12] To exclude other non-RCC renal malignancies, only recognizable histologic subtypes were selected (8140, 8255, 8260, 8270, 8290, 8310, 8312, 8316, 8317-8320, 8323). Inpatient Medicare files for International Classification of Diseases, 9th Revision (ICD-9) procedure claims were used to identify patients managed surgically with PN (55.4) or RN (55.5, 55.51). Patients treated with bilateral nephrectomy (55.54) or those with 2 or more surgical claims within 5 years were excluded. Only patients with localized, nonmetastatic small renal mass (SRM) at presentation were included [Collaborative Stage (CS) Met code 00, CS Lymph Node codes 000 and 999, and CS Tumors size 001-040 and 991-994]. Only SRM were included in the analysis regardless of final pathologic stage.

For each patient, age, sex, race, and treatment year were recorded. Including patients aged ≥66 years allows an additional year in Medicare to capture >85% of comorbidities.[13] Both inpatient and outpatient claims were used to calculate the Charlson comorbidity index as described by Klabunde et al.[14] Individuals with preexisting end-stage renal disease (ESRD) at diagnosis were excluded from analysis.

Control Groups

Patient characteristics differ between PN and RN; therefore, each RCC surgical group was separately matched with control cohorts.[9, 15] Noncancer controls (NCC) were selected from a 5% random sample of Medicare beneficiaries aged ≥66 years and only included individuals without a prior cancer diagnosis at the time of matching. To control for potential nonmeasurable differences between cancer and noncancer patients, a separate cancer control group was included. Non–muscle-invasive bladder cancer was selected due to excellent CSS and a similar follow-up pattern that includes urologist office visits and abdominal imaging. Bladder cancer controls (BCC) were selected using an algorithm established by Chamie et al.[16] This cohort included individuals aged ≥66 years with low-grade (grade 1 or 2), non–muscle-invasive bladder cancer (CS Ta, T1, and Tis) that did not undergo cystectomy. Patients with a prior ESRD diagnosis were excluded.

To perform a matched cohort study, an algorithm was selected to match the treated PN or RN subjects with 2 separate, untreated control groups. The greedy match algorithm was chosen as the method to match the RCC cases with a defined set of controls found in either the 5% Medicare file (NCC) or SEER-Medicare (BCC). With the greedy algorithm, a randomly treated subject is selected and matched with an untreated control subject with the closest propensity score based on defined covariates.[17, 18] Once a match is made, it is not reconsidered as opposed to an alternative technique, the optimal match algorithm. Both these techniques have been compared, and both produce well-balanced matched samples.[17] Patients were matched with controls for age (±3 years), year of diagnosis, race, sex, Charlson comorbidity index, and preexisting hypertension. We chose hypertension as an additional characteristic to match cases because it is not represented in the Charlson comorbidity index. Socioeconomic status (SES) and education were both split into 3 tertiles (high, middle, and low), similar to that described by prior studies.[7, 19]

Primary Outcome Measure

For all cancer groups, follow-up began at the date of surgery. The NCC group's follow-up began the year they were matched, using the first month of Medicare eligibility as the index month. The primary outcome measure OS was calculated from the start of follow-up until the date of death (from the Medicare files) or the last follow-up. OS for each kidney surgery was compared with both controls.

Secondary Outcome Measures

CSS was also calculated for the kidney cancer groups as well as the BCC using SEER data. When differences in OS were noted between groups, the cause of death was extracted from SEER's cause of death variable. We grouped 94 causes of death into 19 related categories to evaluate differences between cancer groups. Because these data were determined from SEER, it therefore was not available for the NCC group.

Statistical Methodology

Chi-square test, analysis of variance, and generalized linear model least square means testing were used to evaluate whether differences existed between cases and respective control groups (NCC and BCC). Although our greedy match algorithm exactly matched patients on several key variables, other factors that may influence survival were included in a multivariate model. It has been established that patients undergoing PN tend to have higher SES and education than RN; therefore, these factors were incorporated into a multivariate Cox model of OS. The Kaplan-Meier method was used to calculate OS and CSS estimates. Differences were calculated using a log-rank test. Additionally, a multivariate Cox proportional hazard model was used to assess the influence of surgical treatment on outcome between the cases and controls.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Study Cohort

We identified a total of 5770 Medicare beneficiaries that met inclusion criteria. A total of 1471 patients were treated with PN, and 4299 patients were treated with RN. For the PN cohort, 1436 NCC and 1471 BCC were identified. For the RN cohort, 4247 NCC and 4299 BCC were identified. As demonstrated in previous studies using SEER-Medicare data, patients undergoing PN had improved OS compared with RN (median survival, 10.45 vs 9.05 years; P<.001) (Fig. 1).[8, 9] PN and RN groups had been matched with BCC and NCC controls by age, sex, race, prior hypertension, and Charlson comorbidity index; therefore, no significant differences were noted (Tables 1 and 2). Neither SES nor education had been used in matching, and differences were noted between groups. PN patients had higher SES than either BCC or NCC (Table 1), and RN patients had higher education compared with NCC (Table 2).

image

Figure 1. Kaplan-Meier estimate of overall survival for partial nephrectomy versus radical nephrectomy.

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Table 1. Partial Nephrectomy and Matched Bladder Cancer and Noncancer Controls
CharacteristicPartial Nephrectomy vs Bladder Cancer ControlsPartial Nephrectomy vs Noncancer Controls
Partial Nephrectomy (n=1471)Bladder Cancer Controls (n=1471)PPartial Nephrectomy (n=1436)Noncancer Controls (n=1436)P
  1. Data are presented as no. (%) unless noted otherwise.

  2. Abbreviations: M, men; W, women.

Age, y  .47  .37
Mean73.2573.38 73.2573.57 
Median7373 7373 
Sex, M/W, no. (% M)875/596 (59.48)875/596 (59.48)1.00818/618 (56.96)818/618 (56.96)1.00
Race  1.00  1.00
White1268 (86.2)1268 (86.2) 1216 (84.68)1216 (84.68) 
Black87 (5.91)87 (5.91) 98 (6.82)98 (6.82) 
Hispanic68 (4.62)68 (4.62) 72 (5.01)72 (5.01) 
Other48 (3.26)48 (3.26) 50 (3.48)50 (3.48) 
Prior hypertension715 (48.61)715 (48.61)1.00694 (48.33)694 (48.33)1.00
Charlson comorbidity index  1.00  1.00
0940 (20.77)940 (20.77) 924 (64.35)924 (64.35) 
1346 (23.52)346 (23.52) 329 (22.91)329 (22.91) 
2106 (7.21)106 (7.21) 112 (7.8)112 (7.8) 
379 (5.37)79 (5.37) 71 (4.94)71 (4.94) 
Socioeconomic status  .023  .002
Low446 (30.32)499 (33.92) 453 (31.55)518 (36.07) 
Medium625 (42.49)630 (42.83) 601 (41.85)610 (42.48) 
High400 (27.19)342 (23.25) 382 (26.6)308 (21.45) 
Education level  .355  .095
Low528 (35.89)491 (33.38) 497 (34.61)490 (34.12) 
Medium604 (41.06)625 (42.49) 593 (41.3)642 (44.71) 
High339 (23.05)355 (24.13) 346 (24.09)304 (21.17) 
Table 2. Radical Nephrectomy and Matched Bladder Cancer and Noncancer Controls
CharacteristicRadical Nephrectomy vs Bladder Cancer ControlsRadical Nephrectomy vs Noncancer Controls
Radical Nephrectomy (n=4299)Bladder Cancer Controls (n=4299)PRadical Nephrectomy (n=4247)Noncancer Controls (n=4247)P
  1. Data are presented as no. (%) unless noted otherwise.

  2. Abbreviations: M, men; W, women.

Age, y  .45  .61
Mean74.8274.91 74.7174.77 
Median7575 7574 
Sex, M/W, no. (% M)2361/1938 (54.92)2361/1938 (54.92)1.002252/1995 (53.03)2252/1995 (53.03)1.00
Race  1.00  1.00
White3751 (87.25)3751 (87.25) 3646 (85.85)3646 (85.85) 
Black244 (5.68)244 (5.68) 272 (6.4)272 (6.4) 
Hispanic185 (4.3)185 (4.3) 198 (4.66)198 (4.66) 
Other119 (2.77)119 (2.77) 131 (3.08)131 (3.08) 
Prior hypertension1836 (42.71)1836 (42.71)1.001819 (42.83)1819 (42.83)1.00
Charlson comorbidity index  1.00  1.00
02787 (64.83)2787 (21.16) 2773 (65.29)2773 (65.29) 
1968 (22.52)968 (22.52) 947 (22.3)947 (22.3) 
2341 (7.93)341 (7.93) 337 (7.94)337 (7.94) 
3203 (4.72)203 (4.72) 190 (4.47)190 (4.47) 
Socioeconomic status  .252  .235
Low1461 (33.98)1406 (32.71) 1468 (34.57)1508 (35.51) 
Medium1910 (44.43)1908 (44.38) 1869 (44.01)1792 (42.19) 
High928 (21.59)985 (22.91) 910 (21.43)947 (22.3) 
Education level  .672  <.0001
Low1377 (32.03)1414 (32.89) 1342 (31.6)1540 (36.26) 
Medium1934 (44.99)1900 (44.2) 1899 (44.71)1756 (41.35) 
High988 (22.98)985 (22.91) 1006 (23.69)951 (22.39) 

As expected, patients with early stage disease had excellent CSS. The 5- and 10-year CSS for the PN, RN, and BCC groups were 98.4% and 97.9%, 97.4% and 95.7%, and 97.4% and 95.8%, respectively. This is similar to other studies showing excellent outcome for the early stage RCC or bladder cancer managed surgically.[20, 21] The median OS of the PN group was 10.45 years, significantly higher than the matched BCC group (8.75 years; P<.001) or the NCC group (8.76 years; P<.001) (Fig. 2a and 2b). The median OS of the RN group was 9.05 years, similar to both the BCC group (8.67 years; P = .067) and the NCC group (8.77 years; P = .49) (Fig. 3a and 3b). The multivariate Cox model of OS for PN versus controls is shown in Table 3. PN had an improvement in OS (hazard ratio [HR], 1.26; P<.001) compared with NCC. Additionally, OS was improved with PN compared with BCC (HR, 1.36; P<.001). The multivariate Cox model of OS for RN versus controls is shown in Table 4. As opposed to an improvement in survival observed with PN, RN offered no significant difference in OS when compared with either NCC (HR, 0.95; P<.139) or BCC (HR, 1.061; P = .066).

image

Figure 2. Overall survival of partial nephrectomy patients compared with (a) bladder cancer control patients and (b) noncancer control patients.

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image

Figure 3. Overall survival of radical nephrectomy patients compared with (a) bladder cancer control patients and (b) noncancer control patients.

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Table 3. Multivariate Cox Model of Overall Survival of Partial Nephrectomy Compared With Noncancer Controls and Bladder Cancer Controls
FactorPartial Nephrectomy vs Noncancer ControlsPartial Nephrectomy vs Bladder Cancer Controls
HR (CI)PHR (CI)P
  1. Abbreviations: CI, confidence interval; HR, hazard ratio.

Partial nephrectomy vs control1.26 (1.102-1.437)<.0011.36 (1.196-1.556)<.001
Socioeconomic status    
Middle vs low0.94 (0.797-1.102).4320.9 (0.768-1.061).214
High vs low0.79 (0.641-0.976).0290.71 (0.575-0.873).001
Education    
Middle vs low0.93 (0.787-1.100).41.07 (0.897-1.267).466
High vs low1.02 (0.835-1.256).821.24 (1.012-1.508).038
Table 4. Multivariate Cox Model of Overall Survival of Radical Nephrectomy Compared With Noncancer Controls and Bladder Cancer Controls
FactorRadical Nephrectomy vs Noncancer ControlsRadical Nephrectomy vs Bladder Cancer Controls
HR (CI)PHR (CI)P
  1. Abbreviations: CI, confidence interval; HR, hazard ratio.

Radical nephrectomy vs control0.95 (0.892-1.016).1391.061 (0.996-1.130).066
Socioeconomic status    
Middle vs low0.87 (0.796-0.939)<.0010.95 (0.873-1.023).163
High vs low0.78 (0.706-0.876)<.0010.86 (0.776-0.950).003
Education    
Middle vs low0.96 (0.883-1.046).3580.98 (0.901-1.062).601
High vs low0.98 (0.879-1.082).6411.07 (0.970-1.182).176

Due to differences in survival between the PN and controls, we performed an exploratory cause of death analysis to determine why PN patients had improved OS; however, a detailed time to event model was not performed. There were 377 and 254 deaths in the BCC and PN groups, respectively (Table 5). The overall causes of death differed significantly between groups (P<.001). Deaths due to thoracic/lung cavity causes (28 vs 80; P<.001) and cardiovascular causes (80 vs 120; P = .003) were proportionally lower in the PN group compared with the BCC group. We had hypothesized that RN would have had worsened OS due to renal and cardiovascular events. However, an exploratory analysis was performed for 1559 and 1457 deaths in the BCC and RN groups, respectively. No difference was observed in the number of cardiovascular events (531 vs 488; P = .151) or renal events (31 vs 37; P = .465) in the BCC and RN groups, respectively.

Table 5. Cause of Death in Partial Nephrectomy and Bladder Cancer Control Groups
CategoryBladder Cancer ControlPartial Nephrectomy
  1. Data are presented as no. (%).

  2. Abbreviation: CNS, central nervous system.

Status  
Alive1094 (74.37)1217 (82.73)
Dead377 (25.63)254 (17.27)
Cause of death  
Larynx and oropharynx1 (0.07)1 (0.07)
Foregut structures12 (0.82)13 (0.88)
Midgut and hindgut6 (0.41)5 (0.34)
Thoracic/Lung cavity80 (5.44)28 (1.90)
Melanoma and other skin diseases1 (0.07)3 (0.20)
Breast3 (0.20)4 (0.27)
Gynecologic3 (0.20)2 (0.14)
Obstetric0 (0)0 (0)
Urologic48 (3.26)27 (1.84)
Diabetes and endocrine disorders9 (0.61)10 (0.68)
Hematologic malignancy6 (0.41)13 (0.88)
Miscellaneous cancer17 (1.16)16 (1.09)
Infectious diseases2 (0.14)2 (0.14)
CNS disorders and Alzheimer disease8 (0.54)11 (0.75)
Cardiovascular120 (8.16)80 (5.44)
Renal failure3 (0.20)12 (0.82)
Congenital anomalies0 (0)0 (0)
Accident, suicide, or homicide4 (0.27)5 (0.34)
Unknown54 (3.67)22 (1.50)
Total14711471

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Our study has several significant findings relevant to the continued uncertainty over the optimal surgical management of the SRM. First, it confirms previous observations based on SEER-Medicare data showing that PN has a significant survival advantage compared with RN. This expected finding of PN having better outcomes than RN highlights how observational studies can inform the debate about optimal management of SRM, yet may be misguided due to the inherent limitations of such data. Second, we demonstrate that RN may not compromise OS based on comparisons with matched BCC and NCC groups. Third, patients who underwent PN had significantly improved OS compared with the matched BCC and NCC control groups (HR of 1.36 and 1.26, respectively). Finally, we explored why OS would be improved with PN and found that thoracic/lung and cardiovascular causes of death were less frequent in the PN group compared with the BCC group.

SEER-Medicare studies repeatedly demonstrate an improvement in survival with PN (Fig. 1), which conflicts with the results of the recent randomized phase 3 EORTC 30904 trial.[6, 7] Because the contrasting studies raise uncertainty over the optimal surgical treatment of the SRM, physicians managing patients diagnosed with SRM must decide whether to rely on level 1 evidence, which may have design flaws, or low-quality evidence from either single institutional or population-based observational data.[22] With continued uncertainty, many academic clinicians have promoted PN to limit adverse renal outcomes associated with RN demonstrated in single institutional and claims-based comparisons.[12, 23] With these concerns in mind, the American Urologic Association issued the “Guideline for the Management of the Clinical T1 Renal Mass” and declared PN the standard of care for healthy patients with a cT1a tumor.[24] In this report, RN was considered an “alternative standard of care if PN is not technically feasible as determined by the urologic surgeon.” Increasing evidence from observational studies reporting the benefits of PN relative to RN and current clinical guidelines have led to increased use of PN over the past decade.[15]

Regardless, we demonstrated that patients undergoing RN did not have worse survival than their matched NCC and BCC controls. This is in contrast to the argument in favor of performing PN to avoid long-term health consequences associated with RN that may worsen survival.[9, 25] Although estimated glomerular filtration rate (GFR) is considered the best indicator of overall renal function, recent evidence suggests that GFR alone may not adequately reflect the extent of kidney disease in a patient with a reduced number of nephrons.[26] A patient with a low GFR after nephrectomy may have fewer long-term cardiovascular risks than a patient with similar GFR, two kidneys, but uncontrolled hypertension and diabetes. This finding is supported by a study of living kidney donors in which patients were not adversely affected by the loss of a kidney.[27] However, one may argue that kidney cancer patients are far different than highly selected renal donors, since many RCC patients have preexisting CKD or are of older age at time of diagnosis, which can be significantly worsened with treatment.[28] Although this may be true, our findings also suggest that RN may pose less harm than believed previously, because OS was similar compared with NCC and BCC controls.

Clinical trials often cannot be undertaken due to ethical, financial, or feasibility concerns. In the absence of a clinical trial, patients and physicians must rely on well-designed observational studies to evaluate the comparative effectiveness of 2 different treatment alternatives for a given disease (in this case, SRM). Multiple studies have shown that PN has improved survival compared with RN.[7, 9, 10, 25] However, observational series are limited by their inability to appropriately control for latent variables that are accounted for in randomized trials. In patients with kidney cancer, multiple unmeasured factors—including body habitus, prior abdominal surgery, and tumor complexity—may influence treatment decisions. Additionally, in observational data, no method can account for the alteration in preoperative planning due to unanticipated, intraoperative findings. This is not an infrequent event, as it occurred in 14.6% of patients randomized to PN who went onto to receive RN in the EORTC 30904 trial. In a randomized trial, this would could be accounted for by cross over, but in observational series in which cross-over data are not available, these patients with more aggressive disease would be identified only in the RN group and could affect both CSS and OS.

Several approaches are available to counter bias that attends analysis of observational data.[29] Propensity scoring approaches and IVA have become more frequent in the recent literature. IVA, which was recently used by Tan et al[7] in their SEER-Medicare comparison of PN versus RN, has the advantage of correcting for both observed and unobserved sources of endogeneity, when the instrument employed is robust. In fact, Tan et al used IVA to test their hypothesis that the survival outcomes reported by EORTC 30904, an actual randomized control trial of PN versus RN, were unreliable due to study limitations. Our data provide another perspective on this puzzle. While greedy algorithm matching does not account for unobserved bias, it is an excellent approach for reducing bias from observed sources. By selecting comparators other than patients undergoing RN, we allow a different inference to be drawn than was possible previously. Because we can identify no biologically plausible reason for patients undergoing PN to have higher OS than their matched counterparts with low-risk bladder cancer or those without cancer, we must conclude that findings regarding OS after PN from prior work using propensity scoring approaches or standard multivariable regression analysis are flawed. The implications of our findings for studies of this topic using IVA are less clear and rest on an appraisal of the performance of the instruments used in such studies.

We performed an exploratory analysis to investigate differences in the cause of death reported by SEER between the PN and BCC groups. Both thoracic/lung cavity and cardiovascular deaths were increased in the BCC groups. Because smoking, the main risk factor for bladder cancer, is unable to be characterized with SEER-Medicare data, it is possible that this greatly influences the results of this comparison and may bias comparisons with RN as well.[11]

Some critics have dismissed the EORTC 30904 trial for its various flaws in favor of observational data supporting PN. We caution against ignoring the level 1 evidence demonstrating that OS is at least equivalent (and perhaps improved) after RN. Although we do not advocate abandoning PN, our data suggest that the survival benefit of PN in observational studies may be based on selection bias. If so, the relegation of RN, with its attendant reduction in perioperative risks compared with PN, to “alternative standard of care” status may merit revisitation by guideline-producing organizations. This matter should be considered before embarking on a planned randomized control trial for clinical stage T1b/2a renal tumors in which OS is considered the primary end point.[30]

Our study has some limitations, including the fact that the SEER-Medicare database is restricted to the elderly population. Because the median age of onset is approximately 64 years, half of the patients with kidney cancer are younger than the patients in our cohort. It is possible that age influences the benefit of nephron-sparing surgery, as younger patients may have more time to develop long-term sequelae from RN.[25] This has been suggested in prior studies demonstrating that improvement in OS may be more pronounced in younger patients and that increased morbidity of PN in the elderly may offset survival advantage.[25, 31] Finally, although we excluded patients with preexisting ESRD at diagnosis, some patients included in the analysis may not have had a normal contralateral kidney.

Conclusions

Although the optimal surgical management of the SRM is frequently debated, both PN and RN options provide excellent CSS. The results of the EORTC 30904 trial and several observational datasets differ in their conclusion regarding the most effective surgical treatment modality. In our analysis of elderly patients diagnosed with RCC in SEER-Medicare data, we demonstrate that RN does not worsen survival compared with matched NCC and BCC groups. Additionally, because PN significantly improved survival compared with similarly matched groups, this finding indicates that the SEER-Medicare observational data are fraught with selection bias that may be impossible to overcome despite the use of analytic methods. Although preservation of renal function is an important concept and we generally advocate for PN, surgical treatment should be individualized on a case-by-case basis. Based on the EORTC 30904 trial and concerns over selection bias with observational data, both RN and PN should be considered a standard of care in the setting of normal overall renal function.

FUNDING SOURCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

The Urologic Disease of America Project is supported by National Institutes of Health grant HHSN276201200016C.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  • 1
    Belldegrun A, Tsui KH, deKernion JB, Smith RB. Efficacy of nephron-sparing surgery for renal cell carcinoma: analysis based on the new 1997 tumor-node-metastasis staging system. J Clin Oncol. 1999;17:2868-2875.
  • 2
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