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- Materals and Methods
- Conflict of Interest
Patient characteristics are summarized in Table 1. Average age at surgery was 62.6 years (median 62.6, range 38.9–80.0). Average BMI was 26.0 kg/m2 (median 25.6, range 17.3–42.0). The majority of patients had no comorbidity (76.0%), a preoperative IPSS score of 0–7 (51.0%) and an IIEF-EF score ≥ 22 (62.2%). Average PSA value was 7.4 ng/mL (median 6.0, range 1.2–54.3). Most patients had a clinical stage T1c (69.7%) and biopsy Gleason score of ≤6 (72.8%). Roughly half of patients received an RRP (56.8%) while the other half received an RALP (43.2%). Most patients received a bilateral nerve-sparing procedure (79.2%). Average surgical volume was 103.2 cases (median 59.5, range 1.0–350.0) for RRP cases and 85.0 cases (median 79.0, range 1.0–222.0) for RALP cases.
Table 1. Descriptive characteristics of 1311 PCa patients treated with NSRP at a single tertiary referral centre between 2000 and 2010.
|Age (years)|| |
|Charlson comorbidity index|| |
|Body mass index (kg/m2)|| |
|Preoperative IPSS|| |
|0–7 (none to mild)||668 (51.0)|
|8–19 (moderate)||497 (37.9)|
|≥20 (severe)||146 (11.1)|
|Preoperative IIEF-EF|| |
|1–10 (severe ED)||291 (22.2)|
|11–17 (moderate ED)||109 (8.3)|
|18–21 (mild to moderate ED)||95 (7.2)|
|22–25 (mild ED)||281 (21.4)|
|≥26 (no ED)||535 (40.8)|
|PSA (ng/mL)|| |
|Clinical stage|| |
|T2 or higher||397 (30.3)|
|Biopsy Gleason score|| |
|Surgery type|| |
|Nerve-sparing type|| |
|Surgical volume for RRP patients*|| |
|Surgical volume for RALP patients†|| |
At 3, 6 and 12 months, the UI rates were 44%, 26% and 12%, respectively. The number of patients at risk was 702, 391 and 162 patients, respectively. The number of patients withdrawing within these intervals (lost to follow-up) was 26, 45 and 66 patients respectively.
All available patient-related covariates were included in the regression tree analysis. The regression tree analysis selected three variables to stratify patients according to their UI risk and estimated the cut-offs that maximized the separation in class-specific survival. These variables consisted of preoperative IIEF-EF (≤10 vs >10 score), age (<65 vs ≥65 years) and BMI (<25 vs ≥25 kg/m2). The stratification process resulted in four UI risk groups (Fig. 1): high (IIEF-EF = 1–10), intermediate (IIEF-EF > 10 and age ≥ 65 years), low (IIEF-EF > 10, age < 65 years and BMI ≥ 25 kg/m2) and very low UI risk (IIEF-EF > 10, age < 65 years and BMI < 25 kg/m2). The 3-month UI rates in these groups were 37%, 43%, 45% and 48%, respectively, the 6-month UI rates were 19%, 23%, 29% and 34%, respectively, and the 12-month UI rates were 7%, 13%, 14% and 15%, respectively. The observed differences in UI rate among these four groups were statistically significant (log-rank test P < 0.001). The area under the curve of this risk classification was 71%, 70% and 68% at 3, 6 and 12 months, respectively.
Figure 1. A novel UI risk classification tool (risk classification tree) based on the data of 1311 patients treated with NSRP between 2006 and 2010 at a single institution.
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Similar trends of UI rate in relation to risk classification were observed when patients were classified according to surgery type (Fig. 2A) and procedure-specific surgical volume (Fig. 2B,C).
Figure 2. A novel UI risk classification tool based on the data of 1311 patients treated with NSRP between 2006 and 2010 at a single institution. Results were stratified according to surgery type (A), the median surgical volume in patients treated with RRP (B) and the median surgical volume in patients treated with RALP (C).
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In patients who were still incontinent 3 months after surgery, the subsequent 3-month UI rates were 51%, 54%, 65% and 71% in patients with very low, low, intermediate and high UI risk, respectively. In patients who were still incontinent 6 months after surgery, the subsequent 6-month UI rates were 34%, 54%, 45% and 47%, respectively (Fig. 3).
Figure 3. A novel UI risk classification tool based on the data of 1311 patients treated with NSRP between 2006 and 2010 at a single institution. Results are shown in terms of conditional estimates for patients that did not recover urinary continence during the first 3 or 6 months after surgery.
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- Materals and Methods
- Conflict of Interest
UI is one of the most disabling surgical sequelae after RP, affecting up to 30% of contemporary patients at long term [7-9, 11, 12, 15, 16]. Previous studies have identified several risk factors associated with a higher postoperative UI risk [9, 11, 12, 15, 16]. However, to date there is no multivariable tool that predicts the postoperative UI rate based on preoperative clinical characteristics. This is crucial, since preoperative individualized predictions of UI would allow for accurate patient counselling aimed at delivering realistic expectations based on baseline patient status. This would in turn optimize patient satisfaction and contribute to maintaining a satisfactory quality of life after surgery. Based on these considerations, we developed and validated a novel preoperative risk classification tool aimed at predicting the risk of UI in patients treated with NSRP.
For the entire cohort, the 3-, 6- and 12-month UI rates were 44%, 26% and 12%, respectively. Regression tree analysis classified patients according to their preoperative characteristics and based on their postoperative UI risk. This process resulted in four UI risk groups, namely high (IIEF-EF = 1–10), intermediate (IIEF-EF > 10 and age ≥ 65 years), low (IIEF-EF > 10, age < 65 years and BMI ≥ 25 kg/m2) and very low (IIEF-EF > 10, age < 65 years and BMI < 25 kg/m2) UI risk. The UI rate across these groups was statistically significantly different.
We opted to stratify our results according to surgeon-related variables (namely type of surgery and procedure-specific surgical volume) rather than including these variables in the risk classification tool. This was because not all centres and/or surgeons can offer both types of surgery (RRP and RALP) and the level of surgical expertise might vary from one centre to another. Such stratification may foster the immediate implication of the novel UI risk tool in clinical practice.
When patients were stratified according to surgery type (Fig. 2A), substantially higher UI rates were observed in RRP patients in comparison with RALP patients, regardless of the UI risk group and/or the examined time endpoint. This might be related to the patient selection process and/or a difference in the postoperative morbidity rate between the two examined procedures. Regardless of the underlying cause, it is noteworthy that the correlation between UI risk classification and the actually observed UI rate holds true for both surgery types. Similar findings were observed when patients were further stratified according to procedure-specific surgical volume (Fig. 2B,C). Intuitively, being operated on by a high volume surgeon was associated with a more favourable UI rate than being operated on by a low volume surgeon. However, the correlation between UI risk classification and the actually observed UI rate holds true regardless of surgical volume.
Recently, we demonstrated the impact of the postoperative elapsed period, defined as the postoperative period in which the patient did not recover urinary continence, on the subsequent UI rate . Intuitively, the longer the postoperative elapsed period without urinary continence recovery, the higher is the subsequent UI risk. The UI rate estimations of our novel tool were adjusted for this factor (Fig. 3). For example, at baseline (immediately after surgery), the 6-month UI rate was 19%, 23%, 29% and 34% in patients with respectively very low, low, intermediate and high UI risk. However, for patients who did not recover their urinary continence during the first three postoperative months, the subsequent 3-month UI rates (a total of 6 months after surgery) increased to respectively 51%, 54%, 65% and 71%. These ‘time-adjusted’ conditional estimates provide more dynamic and realistic results, which might be helpful in informing the patients about their real UI risk in the postoperative period.
Our findings corroborate previous reports. For example, Loeb et al. , Sacco et al.  and Stanford et al.  documented the role of increasing age as a predictor of a higher postoperative UI rate. Similarly, two recent reports [15, 16] that focused on RALP patients showed that age, sexual potency and BMI were independent predictors of the postoperative UI risk. However, none of the previous reports provided a multivariable risk classification tool aimed at prediction of the postoperative UI risk. The present paper addresses this void and provides an accurate UI risk classification tool that can be applied to patients treated with the traditional RRP as well as to patients treated with RALP. Moreover, the estimates provided account for surgical volume as well as elapsed postoperative UI period. This tool might be useful to accurately inform each patient about his postoperative UI risk, thus improving the quality of patient counselling. In our cohort, the risk of long-term UI was the lowest in younger, non-overweight patients with favourable preoperative IIEF-EF values. In consequence, it appears that these individuals may suffer the least from surgical sequelae of RRP such as UI. Similar results have also been obtained when sexual dysfunction was considered as the endpoint . That being said, it may be argued that these individuals represent the optimal candidates for this treatment modality.
Despite these strengths, our study is not without limitations. First, because of the observational nature of our cohort, our findings must be interpreted within the context of the limitations applicable to observational data. Second, we adjusted our analyses for all available covariates. However, other unobserved confounders might have contributed to the observed results. For example, data collection in our cohort was initiated at the time of patient admission to the hospital. Prior to this, all patients were extensively counselled about possible treatment options for PCa, including possible benefits and side effects of each approach. Thus, the decision to undergo RP followed patient and physician discussion about possible treatment options and expectations according to the clinical and oncological profile of each individual patient. However, in our prospectively filled database of surgically treated patients, it was not possible to retrieve functional and quality of life data of patients treated with other forms of therapy for PCa. Therefore, differences in subjective and objective impacts of different forms of therapeutic approaches could not be assessed in our study. It may be argued that some individuals included in our cohort, especially older and/or more overweight subjects, could have benefited from other treatment options potentially associated with more favourable functional outcomes. This limitation is shared with virtually all previous reports that addressed a similar endpoint [9, 11, 12, 15, 16]. Furthermore, our results can be applied only to patients treated with either unilateral or bilateral NSRP. Third, it may be argued that the elevated BMI values (maximum value 42 kg/m2) in some of our patients negatively influenced the UI rate in our cohort. However, the mean value of this covariate in our study is in agreement with previously published surgical series [15, 16]. Moreover, only a minority of the cases in our cohort had an extremely high BMI value (BMI > 30 kg/m2: 8.8%). Fourth, our novel model was based on the ‘best’ predictors of UI in a selected cohort of patients who did not suffer from preoperative UI. This may have contributed to the exclusion of preoperative IPSS score as a predictor of UI, which may seem counterintuitive. Finally, our cohort represents data from a single institution. It remains to be tested whether our findings are applicable to other cohorts. Therefore, a multicentric or a population-based validation of our model is warranted to confirm our results.
In conclusion, we developed and validated the first multivariable risk classification tool based on preoperative patient data that allows an accurate estimation of the postoperative UI rate in patients treated with NSRP. It appears that impotent men before RP as well as elderly and/or overweight patients are those harbouring the highest risk of UI after RP. This tool may significantly help in improving patient counselling as well as in optimizing patients' expectations about their functional status after surgery.