DISCUSSION
The aim of this study was to use a large database focusing on surgical complications to better determine the risks of TURBT specifically when stratified by size of resection. We found that larger tumors (>5 cm) are associated with a higher likelihood of developing postoperative complications (ex: UTI, transfusion, acute renal failure, blood clot, sepsis). Additionally, LOS, reoperation, readmission, and mortality following TURBT were also found to be significantly greater in the large tumor cohort. These results implicate that (not surprisingly) tumor size and resection volume impacts surgical recovery. Therefore, patients should be counseled appropriately prior to undergoing TURBT on the possibility of a longer period of observation prior to discharge as well as the potential for readmission depending on extent of TUR.
TURBT remains the first-line option in the diagnosis and treatment of bladder cancer as well as management of recurrences. Although TURBT is considered an endoscopic and often ambulatory procedure it is not without complications [6]. A large database analysis evaluating morbidity of urological procedures found a TURBT-related complication rate of 11% [7]. A prospective evaluation of all TURBTs performed during a one-year period at an academic center revealed a complication rate of 5.8%. These complications included hematuria requiring transfusion and bladder perforation [8]. Our analysis focusing on over 15,000 TURBT procedures in NSQIP noted a similar complication rate of approximately 6%.
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Specifically, regarding immediate postoperative complications following TURBT, Gregg et al. found the overall complication rate to be 8.1%, with the most common complications being pain/spasm (3%), retention (2.8%), and infection (2.1%). These authors noted that a prior complication and single tumor, but no other patient or tumor-specific characteristic, to be associated with developing a postoperative complication [9]. Similarly, operative duration, has been shown to play an important prognostic role following TURBT. That is, increased operative time is associated with postoperative complication, even after controlling for patient demographic data and tumor characteristics [10].
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There is relative paucity of data directly associating tumor size found on TURBT to the presence of postoperative complications. Ghali et al. conducted a retrospective review of TURBTs performed at a single-center in order to evaluate factors associated with unplanned hospital return [11]. They found an unplanned hospital return rate of 10.9%, most commonly due to hematuria. Their analysis demonstrated that tumor size had no association to an unplanned hospital return following bladder tumor resection. Other authors, however, have observed that tumor size may be a potential risk factor for 30-day and 90-day mortality following TURBT. In their review of the NSQIP database, Hollenbeck et al. found that larger tumors seemed to be associated with a higher postoperative mortality [12]. Our study representing a more contemporary cohort builds on this earlier observation by noting that larger tumors, compared to their smaller counterparts, are associated with a greater risk of postsurgical complications, LOS, reoperation, readmission, and mortality following TURBT.
Although LOS was only extended approximately 0.40 days, these observations may have bearing in a healthcare environment where endoscopic procedures are increasingly performed in outpatient setting. Collectively, we believe these findings underscore the importance of using tumor size as a discussion point for proper informed consent conversation regarding expectations following surgery. This study is not without limitations. The actual sizes of the tumors were unknown due to the nature of categorizing by CPT codes. Therefore, the analysis is subject to variability with respect to how urologists coded specific procedures with potential subjectivity in assessment. As the main focus of this paper is the effect of tumor size on TURBT complications, we did not include the use of intravesical therapy although this may also contribute to complications in a small percentage of patients. Furthermore, reimbursement is stratified according to CPT code and so tumor size is fairly subjective and may be biased by this incentive-based model. Indeed, there is no pathologic information pertaining to the resection and these factors may impact the quality and thoroughness of resection. Furthermore, with regards to reoperation, there may be inadvertent capture of planned repeat TURBTs for further staging of the disease. This may be pertinent to patients with T1 disease or those with larger tumors who have anticipated staged resections. Logistic regression modeling allowed us to assess the impact of multiple variables in the same model. Logistic regression modeling assumes that the selected co-variates are independent of one another. Independent variables in Table 1 were run in logistic regression models against each of the dichotomous variables listed in Table 3. Potential confounders in our multivariate model are the relationship between operative time and tumor size and the association of diabetes with obesity. We acknowledge these as potential confounders but determined that these were not significant enough to preclude logistic regression modeling. Finally, these data do not permit understanding the granularity of cases with regards to therapeutic versus palliative surgery or potential emergent nature of resection. Nonetheless, despite these limitations, we feel the current study has identified and filled a gap in the literature through easily measured metrics, although further study and data is warranted.
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