Journal of the National Cancer Institute Advance Access published online on July 24, 2007
JNCI Journal of the National Cancer Institute, doi:10.1093/jnci/djm060
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ARTICLES |
The Surgical Learning Curve for Prostate Cancer Control After Radical Prostatectomy
Affiliations of authors: Departments of Epidemiology and Biostatistics (AJV, AMS, DS) and Surgery (FJB, JAE, PTS), Memorial Sloan-Kettering Cancer Center, New York, NY; Department of Quantitative Health Sciences (MWK) and Urological Institute (EAK), Cleveland Clinic, Cleveland, OH; Departments of Epidemiology and Biostatistics (AMR) and Urology (JEP), Wayne State University, Detroit, MI
Correspondence to: Andrew J. Vickers, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10021 (e-mail: vickersa{at}mskcc.org).
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ABSTRACT |
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 Top Abstract Context and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
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Background: The learning curve for surgery—i.e., improvement in surgical outcomes with increasing surgeon experience—remains primarily a theoretical concept; actual curves based on surgical outcome data are rarely presented. We analyzed the surgical learning curve for prostate cancer recurrence after radical prostatectomy.
Methods: The study cohort included 7765 prostate cancer patients who were treated with radical prostatectomy by one of 72 surgeons at four major US academic medical centers between 1987 and 2003. For each patient, surgeon experience was coded as the total number of radical prostatectomies performed by the surgeon before the patient’s operation. Multivariable survival–time regression models were used to evaluate the association between surgeon experience and prostate cancer recurrence, defined as a serum prostate-specific antigen (PSA) of more than 0.4 ng/mL followed by a subsequent higher PSA level (i.e., biochemical recurrence), with adjustment for established clinical and tumor characteristics. All P values are two-sided.
Results: The learning curve for prostate cancer recurrence after radical prostatectomy was steep and did not start to plateau until a surgeon had completed approximately 250 prior operations. The predicted probabilities of recurrence at 5 years were 17.9% (95% confidence interval [CI] = 12.1% to 25.6%) for patients treated by surgeons with 10 prior operations and 10.7% (95% CI = 7.1% to 15.9%) for patients treated by surgeons with 250 prior operations (difference = 7.2%, 95% CI = 4.6% to 10.1%; P<.001). This finding was robust to sensitivity analysis; in particular, the results were unaffected if we restricted the sample to patients treated after 1995, when stage migration related to the advent of PSA screening appeared largely complete.
Conclusions: As a surgeon's experience increases, cancer control after radical prostatectomy improves, presumably because of improved surgical technique. Further research is needed to examine the specific techniques used by experienced surgeons that are associated with improved outcomes.
Prior knowledge Surgical outcome is widely believed to depend on the experience of the surgeon, but actual surgical learning curves based on surgical outcome data are rarely presented. Study design An analysis of the association between a surgeon's prior experience with performing radical prostatectomy and biochemical recurrence of prostate cancer (as defined by the serum prostate-specific antigen level) after radical prostatectomy in patients with clinically localized prostate cancer. Contribution Surgical experience was associated with the probability of patients being biochemical recurrence free after radical prostatectomy. Implications The surgical technique of experienced surgeons may differ from that of less experienced surgeons, and opportunities for continued surgical education are needed. Limitations Differences in case mix among surgeons may have contributed to residual confounding. Patient follow-up differed among institutions and surgeons. Accordingly, surgeon experience could not definitively be linked causally to patient outcome in this observational study. Biochemical recurrence is of uncertain clinical relevance to patients.
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The outcome of surgery is generally thought to depend on the experience of the surgeon. Accordingly, the concept of the learning curve is commonly discussed with respect to a variety of surgical techniques (1,2). Nonetheless, the learning curve remains primarily a theoretical concept; actual curves based on surgical outcome data are rarely if ever presented in the literature.
We used individual patient data from four institutions to study the association between a surgeon's prior experience with performing radical prostatectomy and biochemical recurrence of prostate cancer (as defined by the serum prostate-specific antigen [PSA] level) after surgery. This approach allowed us to calculate the surgical learning curve for prostate cancer control after radical prostatectomy. Biochemical recurrence after radical prostatectomy is a good model to study the association between surgeon characteristics and outcome because adjuvant therapy is not commonly given for prostate cancer and recurrence is not substantially affected by other aspects of postoperative care. Moreover, predictive models have been developed that allow statistical adjustment for case mix (3). Thus, differences in outcomes associated with surgeon characteristics, after controlling for case mix, would provide evidence that surgical technique affects outcome.
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Patients and Methods |
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Study Cohort and Data Sources
The study cohort consisted of 9376 patients with clinically localized prostate cancer who were treated by open radical retropubic prostatectomy between January 1987 and December 2003 at one of four participating institutions: Memorial Sloan-Kettering Cancer Center (New York, NY), Baylor College of Medicine (Houston, TX), Wayne State University (Detroit, MI), and the Cleveland Clinic (Cleveland, OH). Patients who received neoadjuvant therapy (n = 1316) or adjuvant therapy (n = 85) or who had missing data for the treating surgeon (n = 144) or for serum PSA level (n = 66) were excluded, leaving a total of 7765 patients eligible for analysis. All information was obtained with appropriate Institutional Review Board waivers, and data were deidentified before analysis.
Eligible patients were treated by one of 72 surgeons, all of whom saw patients only at a study institution while on staff there. Surgeons who had previously conducted radical prostatectomies at a nonstudy institution were asked to provide their prior caseload. A total of 38 surgeons (53%) had performed radical prostatectomies exclusively at a study institution; 22 surgeons (31%) reported that they had performed fewer than 20 radical prostatectomies before conducting their first radical prostatectomy on a study patient; six surgeons (8%) reported that they had performed 20–40 radical prostatectomies, and six (8%) others reported performing more than 40 radical prostatectomies on nonstudy patients; the highest number of radical prostatecomies performed on nonstudy patients was 102. We therefore were able to obtain data on all or almost all of the study surgeons’ patients throughout their careers to date.
Outcomes
Patient follow-up was conducted according to accepted clinical practice at each institution. In general, follow-up consisted of measuring serum PSA levels every 3–4 months during the first year after surgery, semiannually during the second year after surgery, and annually thereafter. Cancer recurrence was defined as a serum PSA of more than 0.4 ng/mL followed by a subsequent higher PSA level (i.e., biochemical recurrence) (4). In rare cases (e.g., <1% in the Memorial Sloan-Kettering Cancer Center dataset), secondary treatment was initiated for patients who did not meet the criteria for recurrence: such treatment was counted as an event. Positive surgical margin status was defined as the presence of tumor cells at the inked margin of resection in the prostatectomy specimen.
Statistical Methods
For each patient, surgeon experience was coded as the number of radical prostatectomies performed by the surgeon before the patient's operation. This number reflects the surgeon's total prior experience, including operations that the surgeon performed at nonstudy institutions and operations involving patients who were ineligible for this analysis. Only a single billing surgeon was recorded for each operation; operations at which a surgeon assisted, such as during fellowship training, were not counted toward the surgeon's prior experience. Thus, surgeon experience differed for each patient treated by a particular surgeon.
For our initial, descriptive analysis, we categorized the patients into one of five groups according to the experience of their surgeon at the time of the patient's radical prostatectomy (<50, 50–99, 100–249, 250–999, or 
1000 prior radical prostatectomies). These cut points were chosen to reflect clinical judgments about different levels of surgeon experience; they are for illustrative purposes only and were not entered into any statistical analyses: hence, our findings are unaffected by the choice of cut points. To evaluate further the association between surgeon experience and biochemical recurrence after radical prostatectomy, we created a multivariable, parametric survival–time regression model in which surgeon experience was entered as a continuous variable. Because the length of follow-up is not independent of surgeon experience, we used a log-logistic survival distribution to model hazard over time. Because the relationship between surgeon experience and biochemical recurrence may be nonlinear, we used restricted cubic splines with knots at the quartiles for modeling the effects of experience. We assumed that only a small number of men would die from causes other than prostate cancer during follow-up and chose a method of analysis such that these men would be censored at the time of death.
To adjust for differences in case mix among surgeons, we included the following covariates in our model: the preoperative PSA level and the pathologic tumor stage and Gleason grade of the surgical specimen. These parameters have been consistently associated with cancer recurrence after radical prostatectomy (3). Race was not included because it is not an independent prognostic factor for biochemical recurrence after radical prostatectomy (5,6). Pathologic tumor stage was entered as the presence or absence of three separate variables: extracapsular extension, seminal vesicle invasion, and lymph node involvement. To adjust for the possibility of stage migration, we included as a covariate the year that the surgery was performed. The degree to which our model corrected for case mix was assessed by the concordance index, which has the same interpretation as the area under the receiver operating characteristic curve but can be evaluated for survival time data. Because data from different patients treated by the same surgeon are not independent, we incorporated within-surgeon clustering into our analyses using a generalized estimating equations approach (7) by specifying the cluster option in Stata statistical software (version 9.2; Stata Corp, College Station, TX). We did not cluster by institution because there is no plausible mechanism for how an institution could modify recurrence rates independent of a surgeon. To produce a learning curve, we used the mean value for covariates to calculate the 5-year recurrence-free probability predicted by the model for each level of surgical experience. Confidence intervals (CIs) for the difference between selected points on the curve were obtained by bootstrapping. All P values are two-sided.
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Results |
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Surgeon and Patient Characteristics by Surgeon Experience
The distribution of surgeons by total number of prostatectomies performed is shown in Table 1. Although most of the surgeons (57%) had performed fewer than 50 prostatectomies during their career to date, a substantial percentage (22%) had performed at least 100 surgeries in total. Clinical and pathologic characteristics of the study cohort are shown in Table 2. Roughly half of the patients (3673 [47%]) were treated by a surgeon who had performed fewer than 250 prior radical prostatectomies; the other half (4092 [53%]) were treated by a surgeon who had performed 250 or more prior radical prostatectomies. Differences in preoperative PSA and age at operation with increasing surgeon experience were small but statistically significant (P = .002 and P<.001, respectively). We observed larger differences in pathologic tumor stage with increasing surgeon experience. These differences appear to be due primarily to stage migration: several surgeons in our dataset treated their first study patients in the late 1980s, when PSA screening was less common and, consequently, the prostate cancers were of more advanced stage than those observed after PSA screening came into widespread use. In our sample, stage migration appeared to be largely complete by 1995, given that the odds ratio per year for non–organ-confined (i.e., advanced) disease was 0.93 (95% CI = 0.90 to 0.97, P<.001) through 1995 and 1.02 (95% CI = 0.99 to 1.05, P = .10) after 1995. Table 3 shows the characteristics of study patients who were treated after 1995. In this subgroup, there was no association between any tumor characteristic and surgeon experience.
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Effect of Surgeon Experience on Cancer Control
There were 1256 biochemical recurrences among the 7765 patients in this study. Median follow-up for patients without recurrence was 3.9 years. Only a small proportion of patients died without experiencing a biochemical recurrence, resulting in a 5-year overall survival probability of 95%. This finding suggests that adjustment for competing risk would have a minimal effect on any of our analyses.
Our initial descriptive analysis revealed that patients who were treated by surgeons with more prior experience had a lower probability of recurrence and a lower rate of positive surgical margins than patients who were treated by surgeons with less prior experience (Table 2; Fig. 1). Because these differences in outcomes may have resulted from differences in case mix, we then fit our prespecified multivariable model, which controls for case mix by adjusting for the year the surgery was performed and for clinical and pathologic variables. The predictive accuracy of the model was high (concordance index of 0.81), suggesting that our multivariable model provides good control for case mix. In the adjusted model, greater surgeon experience was associated with a lower risk of prostate cancer recurrence (P<.001).
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Figure 2 shows the 5-year probability of freedom from biochemical recurrence plotted against surgeon experience, which provides the learning curve for prostate cancer control after radical prostatectomy. There was a dramatic improvement in cancer control with increasing surgeon experience up to 250 prior operations but no large change in recurrence rates with further surgeon experience. To illustrate the association between surgeon experience and outcome, we compared the risk of recurrence for a patient who was treated by a surgeon with limited experience in radical prostatectomy (one with 10 prior operations) with that of a patient who was treated by a more experienced surgeon (one with 250 prior operations). We chose this definition for an experienced surgeon because this number of prior operations is close to the median (275) for patients and is also the number of prior surgeries at which the learning curve started to plateau. The predicted probabilities of recurrence at 5 years were 17.9% (95% CI = 12.1% to 25.6%) for patients treated by surgeons with 10 prior operations and 10.7% (95% CI = 7.1% to 15.9%) for patients treated by surgeons with 250 prior operations, which corresponds to an absolute risk difference of 7.2% (95% CI = 4.6% to 10.1%) and a number needed to harm of 14; that is, for every 14 patients treated by a surgeon with 10 as opposed to 250 prior surgeries, one patient will experience a recurrence as a result.
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We conducted a number of sensitivity analyses to examine the robustness of our findings (Table 4). To check whether stage migration might have affected our results, we repeated our analysis by restricting the sample to patients who were treated after 1995, because in this group there were few differences in tumor characteristics among patients who were treated by surgeons with different levels of experience (Table 3). To estimate the learning curve in a contemporary group of patients, we also carried out an analysis that was restricted to patients who were treated from 2000 through 2003. To account for changes in tumor grading practice during the study period, we added an interaction term between Gleason grade and calendar year of surgery. To account for unmeasured differences in case mix, we restricted the analysis to patients who were at low risk of recurrence [defined as those with organ-confined cancer, Gleason grade
6, and a PSA level <10 ng/mL (8)] because clinically meaningful differences in prognosis are unlikely in this homogenous group. Because it was possible that the relationship between surgeon experience and outcome might be confounded by the ability of individual surgeons to attract patients (i.e., a less capable surgeon who was unable to establish a practice would therefore contribute to the beginning but not the end of the learning curve), we performed additional analyses in which we restricted the sample to patients whose surgeon had performed at least 100 total surgeries and to patients whose surgeon had performed at least 250 total surgeries. Conversely, to examine whether our results were unduly influenced by a few highly experienced surgeons, we restricted the analysis to patients whose surgeon had completed the median number of prior cases (275) or fewer. Because there were some differences in patient age by different levels of surgeon experience, we added patient age as covariate. In addition, because it is possible that our results might have been affected by differences in the intensity of follow-up or in the use of hormonal therapy before patients met the criterion for biochemical recurrence, we performed analyses in which we shifted the date of recurrence in patients treated by surgeons with fewer than 250 cases by 3 months, corresponding to a difference in follow-up of approximately 6 months. We conducted two separate analyses, shifting the date both forward and backward, corresponding to either increased or reduced intensity of follow-up by less experienced surgeons. We also restricted the analysis to the 38 surgeons for whom we had data for the entire course of their career. Finally, we restricted the analysis to patients who were treated at Memorial Sloan-Kettering Cancer Center, where all surgical specimens are reviewed by specialist uropathologists. As shown in Table 4, although there was greater variability in estimates of recurrence rates for analyses that included smaller sample sizes than the main analysis, the relationship between surgeon experience and outcome was statistically significant in all cases. With the obvious exception of the analysis of low-risk patients, the estimates of recurrence-free probability for patients treated by surgeons with 10 and 250 prior prostatectomies fell largely within the 95% confidence intervals of the main analysis. We repeated all sensitivity analyses by using each year from 1990 through 1999 as the cut point for year of surgery and multiples of 10 between 10 and 250 as the cut point for total number of prostatectomies. In all instances, the relationship between surgeon experience and outcome was statistically significant and of similar magnitude as that in the main analysis (data not shown).
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Finally, we investigated whether the rate of positive surgical margins influenced the association between surgeon experience and biochemical recurrence. Adding margin status to the predictive model only slightly attenuated the effect of surgeon experience (absolute risk reduction for surgeons with 250 versus 10 prior surgeries = 5.3% [95% CI = 3.0% to 7.9%]; P = .001). This finding suggests that experienced surgeons may have used techniques beyond the removal of tissue to avoid microscopically positive surgical margins.
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Discussion |
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TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
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Many studies have examined the relationship between surgeon characteristics, such as yearly caseload, and surgical outcomes. However, it is often unclear whether the findings are causally related to differences in surgical technique or result from differences in adjuvant therapy and supportive care. Reported associations between a surgeon's yearly caseload and decreased perioperative mortality (9), lower rates of surgical complications (10–12), and improved overall survival (13) may relate to the ability of busier surgeons to select more experienced anesthesiologists, organize more intensive postoperative care for their patients, or make better referrals for medical therapy and rehabilitation. Apparent differences in surgical outcomes among surgeons may also result from differences in case mix (14).
We found a statistically significant association between surgical experience and the probability of patients being biochemical recurrence–free after radical prostatectomy, which we described in terms of a learning curve. The difference in outcome among patients who were treated by surgeons who were at different points on the learning curve is of clear clinical relevance. These findings likely reflect a true relationship between surgical technique and cancer control.
Our study has several limitations that reflect the retrospective, observational nature of our data. First, although we adjusted for pathologic tumor characteristics, we cannot entirely discount residual confounding by differences in case mix. Such confounding could have resulted from stage migration because calendar time and surgeon experience are associated. However, we adjusted for calendar year of surgery in our models; moreover, our findings did not change substantially if we restricted the analysis to a homogenous group of low-risk patients. In addition, our findings were unchanged when we included only patients treated after 1995, a time period during which we saw no evidence of stage migration and few differences in case mix between the more and less experienced surgeons. The analysis of more recently treated patients also argues against another possible source of confounding, the ability of more experienced surgeons to exercise more discretion in case selection ("cherry picking"). Indeed, there is evidence to suggest that surgeons are not able to accurately predict which patients will experience a recurrence after radical prostatectomy (15). Second, follow-up of patients was not completely standardized among institutions and surgeons. However, it is unlikely that differential follow-up of patients, such as if novice surgeons saw patients more frequently and thus found recurrences early, would explain our findings because a sensitivity analysis that incorporated a correction for intensity of follow-up did not affect our results. A third limitation that applies to any observational study concerns the direction of causality between experience and outcome. Nonetheless, we are confident that our data reflect a learning process ("good surgeons are made"), rather than a selective referral process ("good surgeons are born" and go on to build a large practice) because our results were unchanged if we restricted the analysis to surgeons who had treated more than 250 cases. In other words, even the most experienced surgeons in our dataset had a learning curve. A final limitation is that the outcome of biochemical recurrence is arguably not of direct clinical relevance to patients. However, clinical endpoints such as metastasis are inevitably preceded by biochemical recurrence. Moreover, biochemical recurrence leads to referral for treatments that are associated with important toxic effects: patients who recur after radical prostatectomy are typically treated with pelvic radiation or hormonal therapy, both of which can have a substantial impact on their quality of life.
Our approach to the surgical learning curve is distinct from that of other studies in the literature. Previous studies on the surgical learning curve have typically depended on simple binary comparisons between surgeons with "high" or "low" levels of experience that are defined as, for example, greater or fewer than 70 lifetime procedures (16). Such an approach does not provide adequate information about potential differences in outcome at different levels of "low" experience or about whether outcome continues to improve after a surgeon has reached a "high" level of experience. Authors of these previous studies have rarely, if ever, presented graphs with actual learning curves that are based on their findings. Moreover, previous studies on the surgical learning curve have focused on operative characteristics such as operating time, blood loss, hospital stay, and complications (16–18), rather than on surgical efficacy.
Our results have implications for clinical research, medical education, and clinical practice. With respect to clinical research, our findings suggest that the surgical technique of experienced surgeons may differ from that of surgeons with less experience. It is currently unclear exactly how technique might differ between these groups; systematic research is required to identify the critical aspects of radical prostatectomy that are associated with cancer control. Experienced surgeons might be more likely to thoroughly irrigate the pelvis after the specimen is removed, might dissect more periprostatic tissue adjacent to the prostatic capsule, might remove apical tissue more completely, or might perform a more complete pelvic lymphadenectomy. Furthermore, greater surgeon experience might be associated with decreased operative time and thus reduced opportunity for micrometastatic seeding. We intend to investigate these possibilities in future studies.
Our findings also have implications for education in surgical oncology. Although the successful practice of surgery necessarily presumes a lifetime of learning, the large number of cases required before the learning curve plateaus suggests the need to expand opportunities for training in surgical technique for surgeons in the early years after residency training. During this period, it is particularly important to measure a surgeon's outcomes, provide feedback, and offer opportunities for continuing surgical education. The current emphasis on immediate complications (e.g., in Morbidity and Mortality conferences) needs to be balanced by a focus on surgical efficacy.
The implications of our findings for the clinical care of prostate cancer patients are perhaps more straightforward. Because surgeon experience was strongly associated with yearly caseload, we can reaffirm many of the practical recommendations made by others who have commentated on volume–outcome studies, including calls for regionalization of cancer care at centers of excellence (19), advising patients to choose high volume surgeons (20), and adjusting payment of surgeons on the basis of performance outcomes or participation in programs of quality assessment and improvement (21).
Our results provide support for what has been previously described (20) as an "implication" of volume–outcome studies, which is that good technique is learned and leads to improvements in outcomes. This finding is perhaps not unexpected: few surgeons or patients would be surprised to learn that prostate cancer patients treated by more experienced surgeons have better outcomes than patients who have less experienced surgeons. However, our focus on cancer outcome, the size of the difference in outcome associated with increasing surgical experience, and the large number of cases required before the learning curve starts to plateau, suggests that more serious attention should be paid to the issue of surgical quality.
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Funding |
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TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
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This work was supported by a grant from the National Cancer Institute (P50-CA92629 SPORE grant to P. T. Scardino) and philanthropic grants to P. T. Scardino from the Allbritton Fund and the Koch Foundation.
Funding to pay the Open Access publication charges for this article was provided by MSKCC Department of Surgery.
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NOTES |
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Dr A. J. Vickers and Dr F. J. Bianco would like to be considered as joint first authors on this paper.
The funding bodies had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
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Manuscript received February 13, 2007; revised May 18, 2007; accepted June 13, 2007.
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