ARTICLE

Relation of Hospital Volume to Colostomy Rates and Survival for Patients With Rectal Cancer

David C. Hodgson, Wei Zhang, Alan M. Zaslavsky, Charles S. Fuchs, William E. Wright, John Z. Ayanian

Affiliations of authors: D. C. Hodgson, Department of Radiation Oncology, Princess Margaret Hospital, Toronto, Ontario, Canada, and the Department of Health Policy, Management and Evaluation, University of Toronto, Toronto; W. Zhang, A. M. Zaslavsky, Department of Health Care Policy, Harvard Medical School, Boston, MA; C. S. Fuchs, Division of Medical Oncology, Dana-Farber Cancer Institute, and Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School; W. E. Wright, Cancer Surveillance Section, California Department of Health Services, Sacramento; J. Z. Ayanian, Department of Health Care Policy, Harvard Medical School, and Division of General Medicine, Department of Medicine, Brigham and Women’s Hospital.

Correspondence to: John Z. Ayanian, M.D., M.P.P., Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave., Boston, MA 02115 (e-mail: ayanian{at}hcp.med.harvard.edu).


    ABSTRACT
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Background: Postoperative mortality after some types of cancer surgery is inversely related to the number of operations performed at a hospital (i.e., hospital volume). This study assessed the association of hospital volume with colostomy rates and survival for patients with rectal cancer in a large representative cohort identified from the California Cancer Registry. Methods: We identified 7257 patients diagnosed from January 1, 1994, through December 31, 1997, with stage I–III rectal cancer who underwent surgical resection. Registry data were linked to hospital discharge abstracts and ZIP-code-level data from the 1990 U.S. Census. Associations of hospital volume with permanent colostomy and 30-day mortality were assessed with the Mantel–Haenszel trend test and logistic regression. Overall survival was examined with the Kaplan–Meier method and a multivariable Cox proportional hazards model. Multivariable analyses adjusted for demographic and clinical variables and patient clustering within hospitals. All tests of statistical significance were two-sided. Results: In unadjusted analyses across decreasing quartiles of hospital volume, we observed statistically significant increases in colostomy rates (29.5%, 31.8%, 35.2%, and 36.6%; P<.001) and in 30-day postoperative mortality (1.6%, 1.6%, 2.9%, and 4.8%; P<.001) and a decrease in 2-year survival (83.7%, 83.2%, 80.9%, and 76.6%; P<.001). The adjusted risks of permanent colostomy (odds ratio [OR] = 1.37, 95% confidence interval [CI] = 1.10 to 1.70), 30-day mortality (OR = 2.64, 95% CI = 1.41 to 4.93), and 2-year mortality (hazard ratio = 1.28, 95% CI = 1.15 to 1.44) were greater for patients at hospitals in the lowest volume quartile than for patients at hospitals in the highest volume quartile. Stratification by tumor stage and comorbidity index did not appreciably affect the results. Adjusted colostomy rates varied statistically significantly (P<.001) among individual hospitals independent of volume. Conclusions: Rectal cancer patients who underwent surgery at high-volume hospitals were less likely to have a permanent colostomy and had better survival rates than those treated in low-volume hospitals. Identifying processes of care that contribute to these differences may improve patients’ outcomes in all hospitals.



    INTRODUCTION
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
The number of operations performed in a hospital (i.e., hospital volume) has been associated with outcomes after surgery for cancers of the pancreas, esophagus, prostate, breast, lung, and colon (19). However, the association of hospital volume, treatment, and outcome after surgery for rectal cancer is unresolved. Some studies (1012) have found that patients in high-volume hospitals are more likely to have sphincter-sparing surgery, whereas others (13,14) have found no difference in the type of surgery. Similarly, better postoperative or overall survival among patients undergoing surgery at high-volume hospitals has been reported in some studies (10,15) but not in others (13,14,1619).

Understanding the relation of hospital volume, surgical practice, and outcome is particularly important for rectal cancer, because prior studies have found that the surgical management of this disease has important effects on tumor control (20,21) and quality of life (22). However, interpretation of the available volume–outcome studies for colorectal cancer is complicated by their inadequate statistical power, limited adjustment for comorbidity, older data, or lack of population-based sampling (23,24). In this study, we used a large population-based cohort of patients with rectal cancer in California, identified from the California Cancer Registry (CCR), to examine the association between hospital volume and colostomy rates, postoperative mortality, and overall survival.


    PATIENTS AND METHODS
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Data Sources and Study Cohort

The cohort was identified from the CCR, which is the largest population-based cancer registry for a geographically contiguous area in the world and maintains data quality standards similar to those of the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program1 (25). Unlike hospital-based cancer registries that are limited to patients seeking care at a single institution, population-based registries have the advantage of including all newly diagnosed cancer patients residing in a geographically defined area, thereby enhancing the representativeness and generalizability of studies in population-based registries. The proportion of patients with colorectal cancer detected only by death certificate in California is 1.1%, and 96.6% of cases of colorectal cancer have pathologic confirmation. These quality benchmarks fulfill standards set by the North American Association of Central Cancer Registries (26).

Institutional review boards of the California Department of Health Services, Public Health Institute, Northern California Cancer Center, and Harvard Medical School approved the study protocol, in accordance with assurances filed with and approved by the Department of Health and Human Services. Because our study used existing data from registry records and hospital discharge abstracts with encrypted patient and hospital identifiers to maintain confidentiality, written informed consent from study subjects was not required.

The CCR provided data regarding patients’ age, sex, race, date of diagnosis, tumor site, tumor stage, and number of lymph nodes examined in the surgical specimen. Extent-of-disease codes collected by the CCR were converted into American Joint Committee on Cancer (27) stage with a computer algorithm developed by the SEER program (28). Socioeconomic status was defined by use of the proportion of residents in patients’ census ZIP code with postsecondary education and data from the 1990 U.S. Census.

The study cohort was drawn from all 9843 patients diagnosed in California from January 1, 1994, through December 31, 1997, who met the following two criteria: 1) International Classification of Diseases for Oncology-2 codes 20.9 for rectal cancer or 19.9 for rectosigmoid cancer (29) and 2) tumor stage I–III. Registry data were linked to hospital discharge abstracts and ZIP-code-level data from the 1990 U.S. Census. The 580 patients who could not be linked to ZIP-code-level census data or had missing vital status or hospital identifiers were excluded. For the remaining 9263 patients, we attempted to link CCR data with hospital discharge abstracts maintained by the California Office of Statewide Health Planning and Development, by use of a probabilistic matching algorithm based on the patient’s Social Security number, date of birth, sex, and ZIP code (30). CCR data were successfully linked with discharge abstract data for 7646 (82.5%) of the 9263 patients. Linked patients did not differ statistically significantly from unlinked patients by age or sex, but they were more likely to be white (75.0% versus 70.2%; P = .04) and to have stage II (34.3% versus 24.6%) or stage III (31.8% versus 19.1%) disease (P = .005). Surgical procedures and comorbidity index scores were derived from these hospital discharge abstracts. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure codes were used to determine whether a patient had undergone colostomy (codes 46.01–.03, 46.10–.14; 46.21–.24; 48.5, 48.62, and 49.6). The 389 patients who did not have a procedure code indicating a major surgical procedure were excluded.

The analytic cohort included the remaining 7257 patients who underwent a major surgical resection and had available hospital, demographic, and follow-up data. Discharge diagnosis codes reported from 18 months before to 6 months after patients’ date of diagnosis with rectal cancer were used to estimate the level of comorbid illness with the Deyo modification of the Charlson comorbidity index (31,32).

Outcome Measures

The following three end points were analyzed: permanent colostomy, 30-day postoperative mortality, and overall mortality rate in the 2 years after surgery. A patient was categorized as having a colostomy when any ostomy procedure (including abdominoperineal resection, which necessarily includes colostomy) was coded as the principal surgical procedure from 2 weeks before to 4 months after diagnosis. Procedures that occurred up to 2 weeks before diagnosis were included, because the CCR uses the pathology report date to define the date of diagnosis; in some cases, the surgery that produced the first pathology specimen may have involved the creation of a stoma. Small-bowel ostomies accounted for 3.1% of the ostomy procedures and were included because they were presumably as undesirable for patients as colostomies. A colostomy was defined as permanent if no discharge abstract had an ICD-9-CM procedure code indicating reversal (codes 45.90–.95 and 46.50–.52) within 1 year of diagnosis.

For all patients, vital status was determined through probabilistic matching of the CCR with data from the following sources: California Death Statistical Master File, National Death Index, Medicaid Enrollment File, Medicare Enrollment File, Department of Motor Vehicles License File, California Hospital Discharge Data, Social Security Death Master File, voter registration and voter history file, and the National Change of Address file.

Statistical Analysis

Hospital volume was calculated as the average annual number of rectal cancer patients undergoing surgery in each specific hospital, as recorded in the CCR from January 1, 1994, through December 31, 1997. The volume calculation did not specify types of procedures, and non-cancer-related rectal surgery was not considered in the determination of hospital volume. Volume categories were created by dividing the cohort into quartiles of average annual caseload that contained approximately equal numbers of patients. To examine whether there were any volume threshold effects for the outcomes studied, we divided the hospitals into deciles of volume and inspected the unadjusted rates of each outcome to determine whether the transition between any deciles was associated with a substantial change in outcome.

Descriptive comparisons of the rates of permanent colostomy, 30-day mortality, and 2-year survival were performed with {chi}2 tests for nominal categories (race, sex, and tumor site) and the Mantel–Haenszel trend test for ordinal categories (age, tumor stage, socioeconomic status quartile, hospital volume, and comorbidity index). These same variables were included in multivariable logistic regression models predicting permanent colostomy and 30-day mortality. Age was modeled as a continuous variable; hospital volume, socioeconomic status, tumor stage, and comorbidity index were entered as indicator variables. Generalized estimating equations were used to account for clustering of patients within hospitals.

Two-year survival by quartile of hospital volume was also estimated with the Kaplan–Meier method, and unadjusted comparisons of overall survival rates were performed with the log-rank test. A multivariable Cox proportional hazards model was used to estimate the association between hospital volume and overall mortality over 2 years, including the same variables described above. To evaluate the proportional hazards assumption, we plotted smoothed Schoenfeld residuals against time and found no evidence of a systematic deviation from proportional hazards. Variances in the Cox model were adjusted to account for patient clustering within hospitals by use of the robust inference of Lin and Wei (33).

We repeated survival analyses stratified by tumor stage and comorbidity index to assess the possible interaction between these variables and hospital volume. From prior evidence that the number of lymph nodes examined in the surgical specimen may be associated with survival for stage II patients, we included this variable in the stage-stratified models, by use of previously defined categories (0–4, 5–8, 9–13, >=14 lymph nodes examined) (34). All analyses described above used SAS software (version 8.2; SAS Institute, Cary, NC), and all tests of statistical significance were two-sided.

To estimate the systematic variation in outcomes attributable to individual hospitals, we used MLwiN 2.1 software (35) to fit hierarchical logistic regression models for colostomy and 30-day mortality and a hierarchical proportional hazards model for overall mortality over 2 years, controlling for hospital volume and patient characteristics. We compared the magnitude of the hospital random effects variance, when statistically significant, with the other modeled effects by calculating the odds ratio (OR) corresponding to a difference of one standard deviation of the random effect between otherwise similar hospitals. To demonstrate the potential impact of variation in hospital quality on outcomes for a patient who would be at average risk if at a hospital of average quality for its volume category, we estimated predicted outcomes if that patient were instead at a hospital one standard deviation (on the logit scale) above or below the rate of the average hospital in its volume category.


    RESULTS
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 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Patient Characteristics and Distribution Among Hospitals

Demographic and clinical characteristics of 7257 patients with rectal cancer by quartile of hospital volume are shown in Table 1Go. Surgery for these patients was performed at 367 hospitals in California. The number of operations performed at individual hospitals ranged from one to 113 over 4 years (median = 13; interquartile range = 5–31). Of the 367 hospitals in the sample, 221 (60.2%) had an average of seven or fewer patients with rectal cancer per year, and only 29 (7.9%) hospitals had an average of more than 20 per year.


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Table 1. Characteristics of patients with rectal cancer undergoing surgery in California, 1994–1997, by hospital volume
 
Patients treated in high-volume hospitals were slightly younger with a lower comorbidity index score and higher socioeconomic status than patients treated in low-volume hospitals. A statistically significantly greater number of lymph nodes were examined in surgical specimens from high-volume hospitals (median difference = two lymph nodes), and the tumors of patients in high-volume hospitals were more likely to be classified as stage III. High-volume hospitals were distributed across the population centers of the state, with some concentration of these hospitals in the San Francisco/Oakland and Sacramento regions and none in the more sparsely populated areas.

Colostomy Rates

Of the entire patient cohort, 33.1% underwent a permanent colostomy. The probability of undergoing permanent colostomy increased statistically significantly as hospital volume decreased: patients in the lowest volume quartile had a 7.1% increase in the absolute risk of permanent colostomy compared with those in the highest volume quartile (Table 2Go). In the multivariable analysis, the probability of undergoing permanent colostomy increased as hospital volume decreased (Table 3Go). These probabilities were statistically significantly higher among patients treated at hospitals in which fewer than seven operations per year (OR = 1.37, 95% confidence interval [CI] = 1.10 to 1.70) or 7–13 operations per year (OR = 1.34, 95% CI = 1.06 to 1.69) were performed than among patients treated at hospitals in which an average of more than 20 operations per year were performed. Other variables statistically significantly associated with an increased risk of colostomy in the multivariable analysis were more distal tumor location, lower socioeconomic status, increasing comorbidity index score, advanced tumor stage, and male sex. Asian patients had a lower adjusted risk of colostomy than white patients, but black and Hispanic patients did not differ statistically significantly from white patients for this outcome.


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Table 2. Unadjusted rates of permanent colostomy, postoperative mortality, and 2-year survival among patients with rectal cancer undergoing surgery in California, 1994–1997
 

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Table 3. Multivariable analysis of colostomy risk and mortality among patients undergoing surgery for colorectal cancer in California, 1994–1997
 
Postoperative Mortality

There was a statistically significant inverse association between hospital volume and 30-day mortality (Table 2Go). The 30-day mortality rate was 1.6% among patients undergoing surgery in the highest volume hospitals and increased to 4.8% among patients undergoing surgery in the lowest volume hospitals (P<.001). Low hospital volume (fewer than seven operations per year) remained a statistically significant predictor of 30-day mortality in the multivariable analysis (OR = 2.64, 95% CI = 1.41 to 4.93) compared with the highest volume quartile (Table 3Go). Other factors statistically significantly associated with greater 30-day mortality in the multivariable analysis were older age, male sex, increasing comorbidity index score, and advanced tumor stage. Patient race or ethnicity was not statistically significantly associated with adjusted 30-day postoperative mortality.

Overall Survival

The actuarial estimate of 2-year survival ranged from 83.7% for patients treated in high-volume hospitals to 76.6% among patients treated in the lowest volume category (P<.001) (Table 2Go and Fig. 1Go), with vital status censored for only 0.8% of patients during the 2 years after surgery. In a Cox proportional hazards model, the risk of death increased steadily as hospital volume decreased (Table 3Go). Patients in the lowest quartile of hospital volume had a statistically significantly higher adjusted overall mortality rate than those treated in high-volume hospitals (hazard ratio [HR] = 1.28, 95% CI = 1.15 to 1.44), as did those in the second lowest quartile (HR = 1.17, 95% CI = 1.06 to 1.30). Other factors statistically significantly associated with a higher overall mortality rate in the multivariable model were increasing age, male sex, higher comorbidity index score, more advanced tumor stage, distal tumor location, low socioeconomic status, and black race.



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Fig. 1. Unadjusted survival for patients undergoing surgery for rectal cancer by quartile of hospital procedure volume in California from 1994 through 1997. One-year survival estimates for volume quartiles (highest [>20 patients] to lowest [<7 patients]) are as follows: 92.7% (95% confidence interval [CI] = 91.5% to 93.8%); 92.2% (95% CI = 91.5% to 93.8%), 89.4% (95% CI = 87.9% to 90.8%), and 86.7% (95% CI = 85.0% to 88.3%). Two-year survival estimates for volume quartiles (highest [>20 patients] to lowest [<7 patients]) are as follows: 83.7% (95% CI = 82.0% to 85.4%), 83.2% (95% CI = 81.6% to 84.9%), 80.9% (95% CI = 79.1% to 82.7%), and 76.6% (95% CI = 74.5% to 78.7%) (P<.001, log-rank test).

 
To better quantify the contribution of patient characteristics to the volume–outcome effect seen in descriptive analyses, we compared the magnitude of the volume effect for overall mortality in the multivariable Cox model with that seen in a Cox model of overall mortality with hospital volume as the only independent variable. The covariates in the fully adjusted model accounted for approximately 26% of the unadjusted volume effect in the lowest volume quartile (HR in single-variable model = 1.38, 95% CI = 1.23 to 1.54; HR in full model = 1.28, 95% CI = 1.15 to 1.44) and 37% of the effect in the second-lowest-volume quartile (HR = 1.27, 95% CI = 1.14 to 1.41 versus HR = 1.17, 95% CI = 1.06 to 1.30). Analyses of deciles of volume revealed no clear volume threshold for overall survival for any of the other outcomes studied (data not shown).

Stratified Analyses

After excluding patients with rectosigmoid tumors, the association between hospital volume and colostomy risk, expressed as an OR, remained for decreasing volume quartiles as follows: 1.00 (referent), 1.18 (95% CI = 0.93 to 1.48), 1.32 (95% CI = 1.02 to 1.70), and 1.34 (95% CI = 1.06 to 1.70). Patients in the lowest volume quartile had a greater risk of 30-day mortality, expressed as an OR, although this was not seen for those in the two middle quartiles as follows: 1.00 (referent), 0.87 (95% CI = 0.49 to 1.54), 0.89 (95% CI = 0.52 to 1.52), and 1.87 (95% CI = 1.18 to 2.98). Similarly, in the Cox regression model, the increased risk of overall mortality, expressed as an HR, remained statistically significant in the two lowest volume quartiles as follows: 1.00 (referent), 1.08 (95% CI = 0.95 to 1.22), 1.18 (95% CI = 1.05 to 1.33), and 1.34 (95% CI = 1.17 to 1.53). Because treatment at a high-volume hospital may be particularly beneficial for patients with multiple medical problems, regression models of 30-day mortality and overall survival were stratified by level of comorbidity. The results of these stratified analyses were not substantially different from the primary results. For example, among patients with no comorbidity, treatment in the lowest volume category hospital was still associated with increased adjusted risks of 30-day mortality (OR = 2.25, 95% CI = 1.56 to 4.36) and mortality over 2 years (HR = 1.29, 95% CI = 1.12 to 1.48). For patients with a comorbidity index score of 2 or higher, the volume–outcome effect was similar in magnitude to the effect among patients with no comorbidity for both 30-day mortality (OR = 2.39, 95% CI = 1.16 to 4.92) and overall mortality (HR = 1.27, 95% CI = 0.96 to 1.68).

Similarly, the survival analysis was stratified by tumor stage to examine whether the volume–outcome effect was greater for patients with more advanced disease. Again, there was no clear effect modification. Among patients treated in the lowest volume category, the adjusted HRs for mortality over 2 years for patients with stage I, II, and III disease were 1.25 (95% CI = 1.03 to 1.52), 1.17 (95% CI = 0.95 to 1.45), and 1.40 (95% CI = 1.20 to 1.64), respectively, relative to patients in the highest volume hospitals in stage-stratified models. Including the number of lymph nodes examined as a variable in the Cox models did not substantially attenuate the volume–outcome relationship, although the risk of death in patients with stage I or II disease increased as the number of lymph nodes in the specimen decreased.

Effects of Individual Hospitals

In hierarchical models examining the random effects of individual hospitals, colostomy rates varied substantially (standard deviation of random effects = 0.33, P<.001). A difference of one standard deviation in the random effect had an impact on the predicted probability of colostomy (OR = 1.38, 95% CI = 1.26 to 1.49) comparable to effects of hospital volume or socioeconomic status depicted in Table 3Go. A patient with an average probability (33%) of receiving a permanent colostomy at a hospital of average quality in its volume category would have a substantially higher probability (41%) at a hospital with a rate moderately (one standard deviation) higher than average and a substantially lower probability (26%) at a hospital with a rate moderately (one standard deviation) lower than average, given the same hospital volume and patient characteristics. Random effects variances for the models of 30-day and overall 2-year mortality rate did not differ statistically significantly from zero.


    DISCUSSION
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
This study demonstrated that the risk of permanent colostomy, 30-day mortality, and 2-year mortality were all higher among patients with rectal cancer undergoing surgery at low-volume hospitals than among those at high-volume hospitals. These results have important clinical and policy implications. Several studies have reported substantial impairment in patients’ quality of life after colostomy. Depression, poor social functioning, and sexual dysfunction are more common among patients with intestinal stomas than among those retaining rectal sphincter function (3640). The absolute difference in 2-year overall survival between the highest and lowest hospital volume categories was 7.1%. This improvement in overall survival among patients treated at high-volume hospitals is comparable to the benefit of adjuvant chemotherapy and radiation therapy after resection of locally advanced rectal cancer (4145), both of which are widely accepted as providing clinically important improvements in outcome.

The overall rate of functional sphincter loss in our study was 33.1%, which is higher than overall rates in reports of expert case series (46,47) but comparable to other overall rates in population-based reports of rectal cancer surgery (10,12,13). Among patients treated at hospitals in which the average number of rectal cancer operations performed per year was less than seven, the absolute rate of stoma formation was 7% greater than that among patients treated at hospitals in which more than 20 rectal cancer operations were performed per year. This finding is consistent with those of Simons et al. (10), who studied patients in Los Angeles who underwent rectal cancer surgery from 1988 through 1992, and Beart et al. (11), who studied both colon and rectal cancer patients treated in a selected sample of hospitals in the United States. Both of these studies found that sphincter-preserving surgery was more common in high-volume than in low-volume hospitals. In contrast, Schrag et al. (15) examined the treatment and outcome of 2815 patients with rectal cancer of all stages diagnosed from 1992 through 1996 by use of the SEER–Medicare linked database and found that, although the rate of abdominoperineal resection was 7% higher in low-volume hospitals, this difference was not statistically significant after adjustment for clinical and demographic factors and surgeon volume. Also, in two smaller studies (13,14), no association between hospital volume and the use of abdominoperineal resection was found.

Lower hospital volume was also associated with a greater risk of 30-day mortality and worse overall survival, even after adjustment for clinical factors associated with these outcomes, including age, comorbidity index, and tumor stage. An absolute difference of 3.2% in 30-day mortality was found between the highest and lowest hospital volume quartiles, a percentage similar to that observed in prior population-based studies of patients with colon cancer (1,9). Other studies (16,19) have found statistically nonsignificant differences in postoperative mortality by hospital volume. Two studies (14,15) have reported no association between hospital volume and postoperative mortality, although one study (15) included patients with metastatic or unstaged disease, and another study (14) did not adjust for comorbidity. Our observed effect of hospital volume on overall survival is consistent with the results of other North American population-based studies of colorectal cancer (9,10), although two British studies (14,17) found no effect of hospital volume on survival. The 7.1% absolute difference in overall 2-year mortality between the lowest and highest quartiles of hospital volume in our study was similar to the 6% absolute difference in a recent study (15) of Medicare beneficiaries with rectal cancer in the United States; the latter mortality difference remained statistically significant after adjusting for patients’ demographic and clinical characteristics but was no longer statistically significant after adjusting for surgeon volume.

The mediators of differences in mortality by hospital volume are important to understand. Low-volume hospitals may have higher rates of postoperative complications for rectal cancer, as one study in Germany (12) demonstrated, and these hospitals may also have less optimal staffing and technical resources to treat serious postoperative complications when they occur. In a population-based study of colorectal cancer patients in Maryland (16), it was found that hospital charges and length of stay were inversely related to hospital volume, providing indirect evidence that postoperative complications may be less severe or better managed in high-volume hospitals. In a study by Bach et al. (48) of surgery for lung cancer, increased rates of postoperative complications contributed to, but did not fully explain, worse overall survival among patients treated in low-volume hospitals. We found that fewer lymph nodes were pathologically evaluated in tumors resected in low-volume hospitals, suggesting that staging may be less thorough at these hospitals. Although this finding did not explain the overall survival differences by hospital volume, it may contribute to less use of appropriate adjuvant therapy for patients who undergo surgery at low-volume hospitals.

Major strengths of our study are the generalizability and consistency of findings for three clinically important end points. The statewide cohort from California was derived from a demographically diverse population of approximately 34 million people (12% of the U.S. population), and the analysis was not restricted to Medicare beneficiaries. Consequently, our results are broadly applicable to rectal cancer patients of all ages. Moreover, in contrast to some prior studies (14,17,18) that examined a single outcome such as postoperative mortality, we were able to detect clinically important and statistically significant differences in surgical management, postoperative mortality, and 2-year survival associated with hospital volume. Our results were robust in stratified analyses that focused on patients with more distal tumors or distinguished patients by tumor stage and level of comorbidity.

Limitations of our study may relate to incomplete measures of tumor location, adjuvant therapy, surgeons’ characteristics, or tumor stage. For example, the distance of the tumor from the anorectal junction may be the most important factor determining a patient’s clinical eligibility for sphincter preservation (49). However, high-volume hospitals may not have a greater proportion of patients with proximally located tumors (13). Although it would be useful to know whether the appropriate use of adjuvant therapy contributed to our findings, we did not incorporate adjuvant therapy in the adjusted analysis because the completeness of these registry data is uncertain. Some of the differences in outcomes related to hospital volume or individual hospitals may be the result of the characteristics of surgeons practicing in these hospitals, such as case volume, training, or attitudes about colostomy. Consequently, future research should compare the relative impact of volume with other characteristics of hospitals and surgeons.

Differences in the accuracy of tumor staging could influence survival analyses if high-volume hospitals perform more thorough staging than low-volume hospitals. One previous study (34) found that, for patients with lymph node-negative rectal cancer, a greater number of lymph nodes examined in the surgical specimen was associated with better 5-year survival, presumably because of understaging or undertreatment of patients with fewer lymph nodes examined. As noted above, we found a small but statistically significant association between the number of lymph nodes examined and hospital volume, but a stage-stratified analysis that included this variable did not attenuate the association between hospital volume and survival. Of note, Tepper et al. (34) found that pathologic examination of approximately 14 lymph nodes was required to maximize the accuracy of staging for rectal cancer patients. In our cohort, however, the proportion of cases that met this criterion ranged from 18.6% in the lowest volume quartile to 23.8% in the highest volume quartile, indicating an opportunity for hospitals in all volume categories to improve staging accuracy.

It is important to recognize that categorization of hospitals by volume may conceal a range of outcomes within each category. Hierarchical regression models demonstrated that the difference in colostomy rates between individual hospitals with rates moderately above and below the average rate was greater than the difference between volume categories. Individual small-volume hospitals may provide excellent care and achieve superior outcomes, whereas a large caseload is not necessarily indicative of optimal treatment or outcomes (50,51).

Nonetheless, our results suggest that the morbidity and mortality related to rectal cancer could be substantially reduced if the favorable results achieved at the better high-volume hospitals could be replicated more widely. How to achieve this goal is the subject of considerable debate (5052). Concentrating rectal cancer surgery in high-volume hospitals may improve overall outcomes but limit access to some low-volume hospitals that also produce good results, and geographic and logistic barriers may restrict the benefits of this approach (51).

Identifying processes of care that contribute to these differences may improve patients’ outcomes. The quality of preoperative imaging, anesthesia support, surgical technique, nursing care, surgical pathology reporting, perioperative medical consultations, and access to appropriate ambulatory care and adjuvant therapy may all contribute to the outcomes of patients with rectal cancer. Examining detailed clinical data from patient records would help to identify the processes of care that mediate variations in outcomes by hospital volume and across individual hospitals. Such information would provide a stronger foundation for designing clinically meaningful approaches to assess and improve the quality of care for patients with rectal cancer.


    NOTES
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Supported by Public Health Service grant R01HS09869 (to Harvard Medical School [J. Ayanian]) funded jointly by the Agency for Healthcare Research and Quality, Department of Health and Human Services, and the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. Dr. Hodgson is supported by a Career Scientist Award from the Ontario Ministry of Health and Long Term Care. He also was supported by a Linton Fellowship from the Ontario Medical Association during the conduct of this study.

1 Editor’s note: SEER is a set of geographically defined, population-based, central cancer registries in the United States, operated by local nonprofit organizations under contract to the National Cancer Institute (NCI). Registry data are submitted electronically without personal identifiers to the NCI on a biannual basis, and the NCI makes the data available to the public for scientific research. Back

We thank Mark Allen and Robert Wolf for assistance with database management.


    REFERENCES
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

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Manuscript received September 16, 2002; revised March 13, 2003; accepted March 24, 2003.


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