THE EFFECT OF HOSPITAL VOLUME ON CANCER CONTROL AFTER RADICAL PROSTATECTOMY

0022-5347/05/1736-2094/0 THE JOURNAL OF UROLOGY® Copyright © 2005 by AMERICAN UROLOGICAL ASSOCIATION

Vol. 173, 2094 –2098, June 2005 Printed in U.S.A.

DOI: 10.1097/01.ju.0000158156.80315.fe

THE EFFECT OF HOSPITAL VOLUME ON CANCER CONTROL AFTER RADICAL PROSTATECTOMY L. M. ELLISON, B. J. TROCK, N. R. POE

AND

A. W. PARTIN*

From the Brady Urological Institute, Johns Hopkins Hospital, Baltimore, Maryland

ABSTRACT

Purpose: For complex oncological procedures, hospital volume affects short and long-term patient outcome. We examined the association of hospital volume and long-term cancer control after radical prostatectomy. Materials and Methods: With a cohort study design, we used the Surveillance, Epidemiology and End Results-Medicare linked files to identify a population based sample of men with newly diagnosed prostate cancer treated primarily with radical prostatectomy. Failure of cancer control was defined as the use of postoperative medical or surgical hormone ablation or treatment with radiation therapy more than 6 months after surgery. Results: A total of 12,635 men underwent radical prostatectomy for incident prostate cancer. After adjusting for age, comorbidity, histological grade and clinical stage, the risk of adjuvant therapy was greater among those treated at low (1 to 33 cases) and medium (34 to 61 cases) volume hospitals than at very high (more than 108 cases) volume hospitals (HR 1.25, p ⬍0.001 and HR 1.11, p ⫽0.023 respectively). Conclusions: Patients treated at lower volume institutions are at increased risk of initiation of subsequent adjuvant therapy with radiation therapy, medical hormone ablation or orchiectomy. Noted differences in cancer control provide additional evidence regarding issues surrounding the debate over surgical volume standards for the surgical treatment of prostate cancer. KEY WORDS: prostatic neoplasms, health facility size, outcome assessment

In the mid 1980s many large corporations became intimately involved with the design and delivery of medical coverage for their employees. Because of the rapidly increasing costs of providing benefits, these same corporations, under the auspices of the Leapfrog Group, have attempted to identify key elements that reduce treatment related morbidity and mortality. One of the more sensitive surrogates of high quality surgical care is hospital volume.1 Hospital volume is a particularly important determinant of patient outcome after complex procedures such as coronary artery bypass grafting, esophagectomy and pancreatoduodenectomy.2, 3 There appears to be a linear dose response type relationship for the previously mentioned procedures whereby high surgical volume leads to improved patient outcomes, whereas for less complex procedures there may be little or no association between hospital volume and patient outcome. The driver of improved outcomes at high volume centers is likely the development of critical pathways, proficiency of care and expertise that comes with practice. The literature exploring this relationship with regard to radical prostatectomy for prostate cancer is relatively limited. Perioperative mortality is a rare occurrence at all levels of hospital volume. However, high volume centers have lower rates of resource use than medium or low volume hospitals.4, 5 In addition, the rates of procedures for treatment of incontinence are higher at low and medium volume institutions than at high volume institutions.6 What remains unknown is the impact of hospital volume on long-term outcome. We used the Surveillance, Epidemiology and End Results (SEER)-Medicare database to determine if the number of radical prostatectomies performed at a hospital is associated with long-term cancer control, as measured by the Submitted for publication July 19, 2004. * Financial interest and/or other relationship with Ethicon EndoSurgical, Urologix and Merck. See Editorial on page 1848.

surrogate end point use of adjuvant therapy with medical hormone ablation, orchiectomy or radiation therapy. MATERIALS AND METHODS

Data sources. We used the SEER-Medicare linked files for 1990 to 1999. The SEER cancer registry captures disease specific measures and treatment data on all incident cases within 5 states and 6 metropolitan areas of the United States. The Medicare program provides health care coverage to individuals age 65 years or older. The Medicare claims data capture the majority of inpatient and outpatient medical encounters of its beneficiaries. However, because the Centers for Medicare and Medicaid Services do not provide accurate data regarding the alternative health plans in which some patients are enrolled, we were not able to account for subsequent nonMedicare treatments. Population. A cohort of men was identified within the Medicare files of 5 SEER regions (Arizona, California, Connecticut, Iowa, Utah and Washington State) during 1990 to 1994. These individuals had newly diagnosed prostate cancer and underwent radical prostatectomy (International Classification of Diseases [ICD]-9 60.5) as an initial form of treatment. Patients were excluded from study if coded within the SEER dataset as undergoing combined treatment with radiation therapy and surgery. Patients were not excluded from study if they were treated with neoadjuvant hormone ablation, a common practice at the time. Outcome variable. We determined whether long-term cancer control was associated with hospital volume. We defined the primary outcome variable, failure of cancer control, as the use of hormone ablative therapy (medical or surgical) or radiation therapy more than 6 months after radical prostatectomy. Hormone ablation therapy was captured with the CPT codes for orchiectomy (54520), and the Health Care Finance Administration Current Procedural Coding System

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HOSPITAL VOLUME AND RADICAL PROSTATECTOMY

codes for Lupron™ (J1950, J9217 or J9218), goserelin (J9202) or diethylstilbestrol (J9156). Planning for or treatment with radiation therapy was captured with the CPT codes 77261 to 77499. To maximize the capture of these events we used outpatient, inpatient and physician claims. Predictor variables. Our primary predictor variable was hospital volume. We calculated hospital volume as the count of radical prostatectomies performed at an institution between 1991 and 1994. Rather than identify quartiles of hospital volume from this data set, we used the low (1 to 33), medium (34 to 61), high (62 to 108) and very high (more than 108) volume cut points defined by Begg et al.6 This approach allows our cancer control observations to be contrasted independently with quality of life issues. Our secondary predictor variables included patient level characteristics. From the SEER dataset we used age at diagnosis, histological grade, and pathological stage and survival data. From the Medicare Provider Analysis and Review hospital file we used hospital code, date of surgery, length of stay, CPT and ICD-9. Patient level characteristics were collected and cross-referenced (when possible) from the SEER and Medicare data sets. Baseline Charlson comorbidity scores were calculated from ICD-9 codes for each individual. Competing radiosensitive alternative primary cancers were identified by the presence of an alternate ICD-9 code for prostate cancer within the 1st diagnostic code field and an external beam radiation therapy code in the Health Care Finance Administration Current Procedural Coding System field. Time definitions. Time zero was defined as the date of radical prostatectomy. Failure date was defined as the first occurrence more than 6 months after radical prostatectomy for each code defining the independent variable (hormone ablation or radiation therapy). In the absence of failure, patients were censored at time of death or administratively censored on December 31, 1999. Analysis. Differences in distributions of variables across hospital volume were analyzed with the chi-square test and tests of trend. Hazard ratios associated with hospital volume were examined with Cox proportional hazards modeling. Because analysis of outcomes for subjects within the same hospital may be correlated for reasons unrelated to volume (eg local patterns of screening and access to care, socioeconomic status, referral patterns), we adjusted for clustering on this variable. The output from this approach was compared with conventional regression to determine the influence of extra-binomial variation associated with clustering within hospitals. Improvement in model fit from the addition of independent patient variables was assessed with likelihood ratio tests for nested models. All independent variables were tested for significant interactions with institutional volume. Kaplan-Meier time to event analysis was used to examine differences in rates of use of adjuvant therapy by hospital volume. Observed differences were analyzed using the log rank test. RESULTS

Between 1990 and 1994 we identified 12,635 men who underwent radical prostatectomy as primary treatment for newly diagnosed prostate cancer. Baseline demographics of these patients stratified by hospital volume are presented in table 1. Differences in patient age, while measurable, were not clinically significant. Case mix varied significantly across hospital volume. Low volume centers treated lower grade and stage disease, whereas higher volume hospitals treated patients with higher grade and stage disease. The Charlson scores followed a similar pattern as stage and grade of disease. On the whole low volume institutions treated a healthier cohort of patients. Higher volume hospitals had a larger than expected proportion of patients with Charlson scores greater than 8. Ten-year overall mortality or 10-year pros-

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tate cancer specific mortality did not vary by hospital volume. Overall 35% of patients received some form of adjuvant therapy during the 10-year followup. Stratifying by hospital volume, overall rates of adjuvant therapy ranged from 33% for high volume hospitals to 37% for low volume hospitals. We used proportional hazards modeling to examine the instantaneous risk of receiving adjuvant therapy after radical prostatectomy. Model 1 in table 2 describes the crude risk of adjuvant therapy stratified by hospital volume. Patients treated at low volume institutions had a 17% increased hazard of going on to receive adjuvant therapy compared with those treated at very high volume hospitals (HR 1.17, 95% CI 1.07– 1.27, p ⫽0.001). Models 2 and 3, respectively, show the adjusted risk of adjuvant therapy after accounting for differences in histological grade and pathological stage, and then histological grade, pathological stage, age and Charlson score. The output from these models suggests that patients treated at low volume centers are at a 25% increased risk (HR 1.25, 95% CI 1.14 –1.38, p ⬍0.001) and patients treated at medium volume centers are at a 10% increased risk (HR 1.11, 95% CI 1.01–1.21, p ⫽0.023) of receiving adjuvant therapy compared with those treated at very high volume centers. As expected, histological grade and clinical stage were significant predictors of subsequent treatment with adjuvant therapy. There was a stepwise dose response type relationship of increased risk for each increase in grade or stage. However, Charlson score was unexpectedly a stable predictor of the main outcome variable. The figure demonstrates the cumulative incidence of adjuvant therapy after radical prostatectomy stratified by hospital volume. After stratifying by hospital volume, rates of adjuvant therapy varied for grade and stage (table 3). Hospital volume had a small effect on the use of adjuvant therapy for patients with low grade disease. However, patients treated at low volume hospitals with more advanced grade disease had higher rates of subsequent adjuvant therapy. In addition, patients treated at low volume hospitals had higher rates of adjuvant therapy for each level of clinical stage. DISCUSSION

For patients with prostate cancer treated with radical prostatectomy, hospital volume is an important and strong predictor of subsequent adjuvant treatment. After accounting for case mix differences, patients treated at low volume hospitals had a 25% increase in risk of further therapy and patients treated at medium volume hospitals a 10% increase in risk of further therapy compared with patients treated at very high volume hospitals. Radical prostatectomy is a complex oncological procedure. The data presented demonstrate a problem regarding performance standards for the surgical treatment of prostate cancer. The baseline case mix distribution suggests that low volume centers selected relatively more patients likely to be cured with radical prostatectomy. However, the 10-year followup data show that a larger proportion of patients at lower volume institutions go on to receive adjuvant treatment. The long-term survival of these individuals did not appear to differ from that of those treated at high volume institutions. There are several potential explanations for this observation. First, overall performance at these institutions may reflect poor patient selection. Stratifying volume groups by histological grade and clinical stage showed little volume effect for patients with favorable disease parameters. However, for higher grade and stage disease, significant decreases in performance were noted at lower volume hospitals. Second, higher failure rates result from differences in surgical technique. The only study questioning surgical performance limited its analysis to the risk of complications. Begg et al reported 30 and 60-day mortality as well as 1-year quality of life outcomes.6 They found no difference in mortality by hospital volume. However, patients treated at lower

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HOSPITAL VOLUME AND RADICAL PROSTATECTOMY TABLE 1. Patient and treating hospital characteristics Hospital Vol Low

No. pts/hospital No. pts No. hospitals Mean age (yrs) Charlson score Grade (%): Well Moderate Poor Undifferentiated Unknown Stage (%): Local Regional Distant Unknown Crude adjuvant therapy rate All cause mortality (%) Prostate Ca mortality (%)

p Value

Medium

High

Very High

1–33 1,953 222 69.3 2.9

34–61 2,794 60 69.5 2.9

62–107 3,098 38 69.8 2.9

108–303 4,790 28 70.2 2.9

0.004 0.73

14.2 61.7 21.5 0.4 2.1

10.2 68.1 20.4 0.5 0.8

10.6 67.0 20.7 0.5 1.2

7.1 67.7 23.7 0.4 1.1

⬍0.001

49.3 35.3 0.6 14.8 36.9 15.7 2.7

45.2 39.3 0.4 15.1 33.4 15.7 2.8

44.2 37.8 0.3 17.7 32.8 15.1 2.8

46.8 41.8 0.2 11.2 34.7 15.8 2.8

0.37 0.01 0.85 0.99

TABLE 2. Hazard ratios for the use of adjuvant therapy after radical prostatectomy stratified by hospital volume Model 1

Hospital vol: Very high High Medium Low Grade: Well Moderate Poor Undifferentiated Stage: Local Regional Distant Age Charlson score

Model 2

Model 3

Hazard Ratio

95% CI

p Value

Hazard Ratio

95% CI

p Value

Hazard Ratio

95% CI

p Value

— 1.00 1.05 1.17

0.92–1.09 0.96–1.15 1.06–1.28

0.928 0.244 0.002

— 1.02 1.09 1.24

0.94–1.12 0.99–1.19 1.13–1.37

0.589 0.054 ⬍0.001

— 1.03 1.11 1.25

0.94–1.12 1.01–1.21 1.14–1.38

0.570 0.023 ⬍0.001

— 1.38 2.42 3.97

1.20–1.58 2.09–2.81 2.72–5.79

⬍0.001 ⬍0.001 ⬍0.001

— 1.37 2.25 3.12

1.19–1.58 1.94–2.60 2.13–4.57

⬍0.001 ⬍0.001 ⬍0.001

— 1.63 4.01

1.53–1.75 2.76–5.85

⬍0.001 ⬍0.001

— 1.51 3.24 1.00 1.07

1.40–1.62 2.23–4.73 0.99–1.01 1.06–1.08

⬍0.001 ⬍0.001 0.497 ⬍0.001

volume hospitals were more likely to undergo procedures for correction of urinary complications. Urinary complications result from compromise of the smooth and striated urinary sphincter. The failure to appreciate anatomical landmarks that results in this morbidity may also lead to increased rates of positive surgical margins. Finally, the increased risk of adjuvant therapy may represent differences in thresholds for the initiation of adjuvant

therapy. Best practice guidelines do not exist for localized prostate cancer. Also absent are standard recommendations for the treatment of patients with biochemical failure. However, it is well documented in the literature that an increasing prostate specific antigen (PSA) is a poor prognostic indicator and, as such, has become a general trigger for further local or systemic therapy. The unspoken alternative explanation may be that for some physicians, financial consider-

Cumulative incidence of initiation of adjuvant hormone ablation therapy or external beam radiation therapy stratified by hospital volume.

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HOSPITAL VOLUME AND RADICAL PROSTATECTOMY TABLE 3. Rates of adjuvant therapy by hospital volume, stratified by histological grade and pathological stage Hospital Vol

Grade (%): Well Moderate Poor Undifferentiated Stage (%): Local Regional Distant Unknown

p Value

Low

Medium

High

Very High

23.8 37.5 54.7 83.3

25.7 33.4 50.4 53.8

21.4 33.5 47.9 66.6

24.1 30.5 53.2 68.4

⬍0.001

31.9 47.7 70.0 44.8

26.9 44.4 72.7 41.4

27.7 41.4 75.0 42.1

26.9 42.8 63.6 45.9

⬍0.001

ations may drive the decision to begin early adjuvant therapy. In 1997 medical hormone ablation accounted for 64% of Medicare reimbursement to urologists for all urological care.7 The relationship of short-term patient outcome after radical prostatectomy and hospital volume has been examined. Ellison et al used the Nationwide Inpatient Sample to examine the relationship between hospital volume and short-term outcome. The in-hospital mortality rate was 0.3% at low and medium volume centers, and 0.17% at high volume centers.4 In addition, length of stay was shorter and hospital charges lower at high volume hospitals. Begg et al found similar differences in mortality measures as well as differences in quality of life indicators by hospital volume.6 The authors suggested that these findings, while important, did not reach a magnitude to prompt regionalization of the surgical treatment of prostate cancer. As estimated by the Charlson index, comorbidity was a modest predictor of treatment failure. There are a number of other malignancies for which the Charlson score has been a predictor of disease specific outcome.8⫺11 Notably patients with bladder cancer who undergo cystectomy have been found to fare worse with higher pretreatment Charlson scores.8 For our study there was a larger than expected proportion of patients at high volume institutions with Charlson scores greater than 8. This follows the overall findings of this study that patients at low volume hospitals, despite better disease parameters, had higher rates of treatment failure. Is there now enough evidence to recommend regionalization of this surgical procedure? Traditionally the decision to regionalize a procedure has related to significant observed differences in hard outcomes (30-day, 60-day or 1-year mortality). For cardiothoracic procedures, the evidence was overwhelming.12⫺15 For pancreatectomy and esophagectomy recent evidence suggests that these procedures may also soon come under more significant regulation.2, 3, 16 –19 For prostate cancer the same end points have not shown the same magnitude of effect. However, prostate cancer is a more indolent disease. Patients are treated to avoid morbidity and mortality that may not be expected for many years. A more appropriate measure may be the impact of failure of cancer control. If such a shift of consensus occurred, then a debate regarding regionalization would be appropriate. Administrative databases are an important resource for health services research. However, because the data were collected for reasons other than answering specific research questions, the conclusions must be balanced with caveats. We posit that coding for adjuvant therapy in an administrative database such as Medicare is a reasonable surrogate for biochemical failure after radical prostatectomy. Certainly advanced disease can be diagnosed by local recurrence on rectal examination or bone metastasis on bone scan. However, PSA is an accurate biochemical marker that becomes detectible in the serum long before clinical manifestations arise. As such PSA has come to serve as the primary surveillance and decision tool for the management of prostate cancer after radical prostatectomy. The Medicare database does not include the clinical values

associated with coded occurrences of PSA testing. However, we believe that the initiation of adjuvant therapy 6 months or more after radical prostatectomy indicates a treatment failure of important magnitude. Unfortunately our analysis is not able to differentiate those patients who are receiving additional therapy as a result of logical management of biochemical recurrence from those not being treated properly for unscrupulous financial reasons. CONCLUSIONS

The number of procedures done at an institution is an important predictor of failure of cancer control as measured by subsequent treatment with adjuvant hormone ablation or radiation therapy. Based on this metric, low and medium volume hospitals fail to achieve the same results as high and very high volume institutions. While adjuvant therapy is used more frequently at low volume institutions, there does not appear to be a difference in overall survival for these patients. This adverse performance has significant costs in the form of decreased patient quality of life as well as increased financial burdens to society. While it is clear that these data would not support regionalization of this procedure to high volume centers, it may be reasonable to recommend minimum volume standards to urologists who wish to continue treating patients with prostate cancer with radical prostatectomy. REFERENCES

1. Luft, H. S., Hunt, S. S. and Maerki, S. C.: The volume-outcome relationship: practice-makes-perfect or selective-referral patterns? Health Serv Res, 22: 157, 1987 2. Birkmeyer, J. D., Warshaw, A. L., Finlayson, S. R., Grove, M. R. and Tosteson, A. N.: Relationship between hospital volume and late survival after pancreaticoduodenectomy. Surgery, 126: 178, 1999 3. Begg, C. B., Cramer, L. D., Hoskins, W. J. and Brennan, M. F.: Impact of hospital volume on operative mortality for major cancer surgery. JAMA, 280: 1747, 1998 4. Ellison, L. M., Heaney, J. A. and Birkmeyer, J. D.: The effect of hospital volume on mortality and resource use after radical prostatectomy. J Urol, 163: 867, 2000 5. Yao, S. L. and Lu-Yao, G.: Population-based study of relationships between hospital volume of prostatectomies, patient outcomes, and length of hospital stay. J Natl Cancer Inst, 91: 1950, 1999 6. Begg, C. B., Riedel, E. R., Bach, P. B., Kattan, M. W., Schrag, D., Warren, J. L. et al: Variations in morbidity after radical prostatectomy. N Engl J Med, 346: 1138, 2002 7. Holtgrewe, H. L.: The economics of prostate cancer. In: Prostate Cancer. Edited by L. Denis. Plymouth, United Kingdom: Health Publications Ltd., pp. 497–514, 2000 8. Miller, D. C., Taub, D. A., Dunn, R. L., Montie, J. E. and Wei, J. T.: The impact of co-morbid disease on cancer control and survival following radical cystectomy. J Urol, 169: 105, 2003 9. Froehner, M., Koch, R., Litz, R., Heller, A., Oehlschlaeger, S. and Wirth, M. P.: Comparison of the American Society of Anesthesiologists Physical Status classification with the Charlson score as predictors of survival after radical prostatectomy. Urology, 62: 698, 2003 10. Gettman, M. T., Boelter, C. W., Cheville, J. C., Zincke, H.,

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11. 12.

13.

14.

HOSPITAL VOLUME AND RADICAL PROSTATECTOMY

Bryant, S. C. and Blute, M. L.: Charlson co-morbidity index as a predictor of outcome after surgery for renal cell carcinoma with renal vein, vena cava or right atrium extension. J Urol, 169: 1282, 2003 Tammemagi, C. M., Neslund-Dudas, C., Simoff, M. and Kvale, P.: Impact of comorbidity on lung cancer survival. Int J Cancer, 103: 792, 2003 Hannan, E. L., Siu, A. L., Kumar, D., Kilburn, H., Jr. and Chassin, M. R.: The decline in coronary artery bypass graft surgery mortality in New York State. The role of surgeon volume. JAMA, 273: 209, 1995 McGrath, P. D., Wennberg, D. E., Dickens, J. D., Jr., Siewers, A. E., Lucas, F. L., Malenka, D. J. et al: Relation between operator and hospital volume and outcomes following percutaneous coronary interventions in the era of the coronary stent. JAMA, 284: 3139, 2000 Bach, P. B., Cramer, L. D., Schrag, D., Downey, R. J., Gelfand, S. E. and Begg, C. B.: The influence of hospital volume on survival after resection for lung cancer. N Engl J Med, 345: 181, 2001

15. Yusen, R. D., Lefrak, S. S., Gierada, D. S., Davis, G. E., Meyers, B. F., Patterson, G. A. et al: A prospective evaluation of lung volume reduction surgery in 200 consecutive patients. Chest, 123: 1026, 2003 16. Dimick, J. B., Cowan, J. A., Jr., Knol, J. A. and Upchurch, G. R., Jr.: Hepatic resection in the United States: indications, outcomes, and hospital procedural volumes from a nationally representative database. Arch Surg, 138: 185, 2003 17. Bachmann, M. O., Alderson, D., Peters, T. J., Bedford, C., Edwards, D., Wotton, S. et al: Influence of specialization on the management and outcome of patients with pancreatic cancer. Br J Surg, 90: 171, 2003 18. Glasgow, R. E., Showstack, J. A., Katz, P. P., Corvera, C. U., Warren, R. S. and Mulvihill, S. J.: The relationship between hospital volume and outcomes of hepatic resection for hepatocellular carcinoma. Arch Surg, 134: 30, 1999 19. Choti, M. A., Bowman, H. M., Pitt, H. A., Sosa, J. A., Sitzmann, J. V., Cameron, J. L. et al: Should hepatic resections be performed at high-volume referral centers? J Gastrointest Surg, 2: 11, 1998