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J Natl Cancer Inst. Apr 15, 2009; 101(8): 571–580.
Published online Apr 15, 2009. doi:  10.1093/jnci/djp039
PMCID: PMC2669100
Provider Treatment Intensity and Outcomes for Patients With Early-Stage Bladder Cancer
Brent K. Hollenbeck,corresponding author Zaojun Ye, Rodney L. Dunn, James E. Montie, and John D. Birkmeyer
Affiliations of authors: Division of Oncology, Department of Urology (BKH, JEM), Division of Health Services Research, Department of Urology (BKH, ZY, RLD, JEM), Department of Surgery (JDB), and Michigan Surgical Collaborative for Outcomes Research and Evaluation (BKH, JDB), University of Michigan Health System, Ann Arbor, MI
corresponding authorCorresponding author.
Correspondence to: Brent K. Hollenbeck, MD, MS, Division of Oncology, Department of Urology, University of Michigan Health System, 1500 East Medical Center Dr, TC 3875, Ann Arbor, MI 48109 (e-mail: bhollen/at/umich.edu).
Received November 5, 2008; Revised January 9, 2009; Accepted February 2, 2009.
Background
Bladder cancer is among the most prevalent and expensive to treat cancers in the United States. In the absence of high-level evidence to guide the optimal management of bladder cancer, urologists may vary widely in how aggressively they treat early-stage disease. We examined associations between initial treatment intensity and subsequent outcomes.
Methods
We used the Surveillance, Epidemiology, and End Results–Medicare database to identify patients who were diagnosed with early-stage bladder cancer from January 1, 1992, through December 31, 2002 (n = 20 713), and the physician primarily responsible for providing care to each patient (n = 940). We ranked the providers according to the intensity of treatment they delivered to their patients (as measured by their average bladder cancer expenditures reported to Medicare in the first 2 years after a diagnosis) and then grouped them into quartiles that contained approximately equal numbers of patients. We assessed associations between treatment intensity and outcomes, including survival through December 31, 2005, and the need for subsequent major interventions by using Cox proportional hazards models. All statistical tests were two-sided.
Results
The average Medicare expenditure per patient for providers in the highest quartile of treatment intensity was more than twice that for providers in the lowest quartile of treatment intensity ($7131 vs $2830, respectively). High–treatment intensity providers more commonly performed endoscopic surveillance and used more intravesical therapy and imaging studies than low–treatment intensity providers. However, the intensity of initial treatment was not associated with a lower risk of mortality (adjusted hazard ratio of death from any cause for patients of low– vs high–treatment intensity providers = 1.03, 95% confidence interval 0.97 to 1.09). Initial intensive management did not obviate the need for later interventions. In fact, a higher proportion of patients treated by high–treatment intensity providers than by low–treatment intensity providers subsequently underwent a major medical intervention (11.0% vs 6.4%, P = .02).
Conclusions
Providers vary widely in how aggressively they manage early-stage bladder cancer. Patients treated by high–treatment intensity providers do not appear to benefit in terms of survival or in avoidance of subsequent major medical interventions.
CONTEXT AND CAVEATS
Prior knowledge
Little is known about how urologists vary in the aggressiveness with which they treat patients during the first 2 years after a diagnosis of early-stage bladder cancer.
Study design
Linked Surveillance, Epidemiology, and End Results (SEER)–Medicare data were used to identify patients who were diagnosed with early-stage bladder cancer and the physician primarily responsible for each patient's care and to examine associations between initial treatment intensity and subsequent outcomes, including survival.
Contribution
Urologists who provided the most aggressive treatment had, on average, more than double the Medicare expenditures per patient compared with those who provided the least aggressive treatment, but their patients did not appear to benefit in terms of survival or in avoidance of subsequent major medical interventions.
Implications
It may be possible to eliminate unnecessary procedures and thus reduce the costs of caring for patients with early-stage bladder cancer.
Limitations
The use of observational data did not allow the authors to account for unmeasured differences between patients in different treatment intensity groups. The use of SEER–Medicare data limits the generalizabity of the finding to patients older than 65 years.
From the Editors
Bladder cancer is the fifth most common new cancer diagnosis and among the most expensive cancers to treat in the United States (1). Nearly three-quarters of incident cases of bladder cancer are non–muscle-invasive (ie, early-stage) tumors (2), which are removed endoscopically. In up to half of these patients, the disease will progress to muscle-invasive cancer (36). Because mortality from muscle-invasive disease is common (7,8) and often requires a major medical intervention (radical cystectomy, systemic chemotherapy, and/or radiation therapy), effective strategies for the prevention and early detection of disease progression are of paramount importance.
How best to achieve this goal remains unclear. Common strategies for bladder cancer surveillance and treatment that may be useful include intensive intravesical therapy, repeat endoscopic resection after diagnosis, and frequent endoscopic surveillance (9,10). However, evidence from randomized clinical trials establishing the optimal approaches to bladder cancer surveillance and treatment is largely lacking. Rather, current guidelines for the surveillance and treatment of early-stage bladder cancer are most commonly based on the opinions of experts or on observational data and generally favor more intensive regimens (10). Consequently, urologists vary widely in how they approach early-stage bladder cancer.
In this context, we used linked Surveillance, Epidemiology, and End Results (SEER)–Medicare data to identify differences in the practice styles of US urologists during the first 2 years after an early-stage bladder cancer diagnosis. We were particularly interested in the extent to which the initial treatment intensity of urologists was associated with patients' outcomes.
Study Population
We used 1992–2005 SEER–Medicare linked data to identify a cohort of patients with early-stage bladder cancer. As detailed elsewhere (11), the files in this database provide a rich source of information on Medicare patients included in SEER, a nationally representative collection of population-based registries that collect information about all incident cancer patients from diverse geographic areas in the United States. By December 31, 2005, the SEER registries included approximately 26% of the US population (12). For each Medicare patient in SEER, the SEER-Medicare–linked files contain 100% of the Medicare claims from the inpatient, outpatient, and national claims history files.
We first identified all Medicare patients aged 65–99 years who had an incident bladder cancer detected before death between January 1, 1992, and December 31, 2002, as documented by bladder cancer codes 67.0–67.9 within the SEER–Medicare Patient Entitlement and Diagnosis Summary File. Next, we limited our study population to patients with early-stage bladder cancer [stage 0 or 1, defined according to the modified American Joint Commission on Cancer (AJCC) (13)] by using specific codes provided by SEER.
To ascertain the physician who had the primary responsibility for each patient's bladder cancer care, we first identified all early-stage bladder cancer–related procedures [as listed in the appendix of Schrag et al. (14)] that were performed within a 2-year period following the patient's diagnosis. Only claims for procedures that were performed for a primary diagnosis of bladder cancer were included. Next, we assigned each patient to the provider who had submitted the most of these Medicare procedure claims for the patient by using the Unique Physician Identifier Number. To ensure adequate reliability in our profiles of individual physician practice styles, we included only those providers who had treated at least 10 patients diagnosed with bladder cancer between January 1, 1992, and December 31, 2002. Using this method, our final study population consisted of 20 713 patients who were treated by 940 providers, 99.4% of whom were urologists.
Characterization of Treatment Intensity
Treatment intensity was defined in terms of early-stage bladder cancer expenditures, which were measured at the patient level and included inpatient and outpatient Medicare payments incurred within the first 2 years after bladder cancer diagnosis. We included only those expenditures that were associated with a primary diagnosis code for bladder cancer [ie, International Classification of Diseases, 9th Revision (ICD-9) (15) codes 188.x (bladder cancer), 233.7 (carcinoma in situ of the bladder), and V105.4 (personal history of bladder cancer)]. Payments were standardized to account for the regional variation in Medicare reimbursement (16). Expenditures related to systemic chemotherapy, radiation therapy, and those incurred after these interventions were not included. Because radical cystectomy is generally considered an effective treatment for patients with high-risk early-stage bladder cancer (17,18), expenditures related to cystectomy were included. All payments were price adjusted to 2005 dollars by using the Medicare Economic Index (16), and the sum of the price-adjusted payments was attributed to the primary bladder cancer care provider. The providers were first ranked according to their average expenditures for the 2-year period after the patients' bladder cancer diagnosis and then sorted into four treatment intensity groups (quartiles) that contained approximately the same number of patients per quartile.
To explore the practice patterns underlying treatment intensity, we characterized processes of care by using the ICD-9 and Healthcare Common Procedure Coding System (HCPCS) codes in the Medicare files. The HCPCS codes are composed primarily of Common Procedure Terminology codes (19) in addition to codes used exclusively by Medicare. For this study, we focused on processes of care that were plausibly relevant to surveillance and survival. As shown in the Appendix, we divided our process-of-care measures into three categories: surveillance related (including endoscopic examination of the bladder, upper urinary tract evaluation, urinary studies, and imaging studies), treatment related (including intravesical therapy and repeat endoscopic resection within 60 days of the initial resection), and medical services (including visits to the urologist and visits to other physicians).
Outcomes
For all outcome measures, we used the patient as the unit of analysis. The primary outcome was all-cause mortality, which avoided potential problems with misclassification of the cause of death (2024) and was measured from January 1, 1992, through December 31, 2005, by using explicit vital status fields in SEER. However, because the vast majority of patients with early-stage bladder cancer are likely to die from competing causes (6), we also assessed bladder cancer–specific mortality as a secondary outcome by using the cause-of-death field available in SEER. Finally, we assessed the patient's need for a subsequent major medical intervention as evidenced by their treatment with radical cystectomy, systemic chemotherapy, and radiation therapy. These major interventions were identified using the appropriate ICD-9 and HCPCS codes within the inpatient, national claims history, and outpatient files.
Statistical Analysis
For all of the analyses, the exposure was provider treatment intensity, which was categorized as quartiles of patients. We first sought to understand differences in patient demographics and disease characteristics according to provider treatment intensity. Next, we characterized the practice styles of these providers by exploring associations between treatment intensity and processes of care. For all of these comparisons, statistical inference was made using chi-square and Kruskal–Wallis tests for categorical and continuous data, respectively.
To examine the association between treatment intensity and survival, we fit a Cox proportional hazards model by adjusting for patient and disease characteristics, including patient age (in 5-year age groups), sex, race (white, black, or other), the International Classification of Diseases for Oncology, 2nd edition (ICD-O-2) (25) tumor grade (low, high, or unknown), and the AJCC (13) tumor stage (Ta, Tis, T1, or Ta or T1 not otherwise specified). In addition, we adjusted for socioeconomic status by using a composite measure that was assessed at the level of the patient's ZIP code, as described by Diez Roux et al. (26). Patients were separated into three equally sized groups of socioeconomic status according to the summary score for this composite measure: low (score range = −12.23 to 1.19), medium (score range = 1.20 to 5.89), and high (score range = 5.90 to 20.76). Patient comorbidities were identified by using ICD-9 diagnosis codes (15) in Medicare inpatient and outpatient claims for health care encounters that had occurred during the 12-month period preceding the bladder cancer diagnosis. We used the Klabunde et al. (27) adaptation of the Charlson comorbidity index (28) to assess comorbidity. Patients were classified according to their comorbidity index score (0, 1, 2, or ≥3), which was treated as a categorical variable. Because patients who were treated by the same provider may have similar outcomes (29), we adjusted the models to account for this potential clustering by using more robust standard errors (30). Briefly, within-cluster correlations in mortality were used to derive variance–covariance estimators. These sandwich estimators were then incorporated into the Cox proportional hazards models that measured the associations between treatment intensity and outcomes. For all Cox models, we confirmed the assumption of proportionality by visual inspection of the hazard plots and by goodness-of-fit testing (31).
For the secondary outcomes (use of cystectomy, systemic chemotherapy, and/or radiation therapy), we fit logistic models to estimate the association between provider treatment intensity and patient-level outcome, by adjusting for patient age (5-year age groups), sex, race (white, black, or other), comorbidity (0, 1, 2, or ≥3), socioeconomic status (low, medium, or high), the ICD-O-2 tumor grade (low, high, or unknown), and the AJCC stage (Ta, Tis, T1, or Ta or T1 not otherwise specified). We computed adjusted percentages for each outcome by back-transforming the predicted use of the intervention from the logistic model. To examine the association between the use of a therapy and provider treatment intensity, Cox proportional hazards models were used to take into account the timing of the therapy while adjusting for the covariates.
To account for potential unmeasured confounding by disease severity (ie, patients who received more intensive treatment may have had more aggressive disease), we conducted a sensitivity analysis in which initial treatment intensity and patient survival were measured in separate populations. For this analysis, treatment intensity was assessed by profiling the providers' practice patterns using data from January 1, 1992, through December 31, 1998, and survival was then assessed among the same providers' patients who were diagnosed with early-stage bladder cancer between January 1, 1999, and December 31, 2002.
All analyses were carried out with SAS software (version 9.1; Cary, NC). All statistical tests were two-tailed, and the probability of a type I error was set at .05. The study protocol was approved by the institutional review board of the University of Michigan.
Medicare expenditures for the initial management of early-stage bladder cancer varied by more than twofold among quartiles of provider treatment intensity and ranged from mean per-patient expenditures of $2830 for low–treatment intensity providers to $7131 for high–treatment intensity providers. Table 1 presents clinical and disease characteristics as the average percentage of patients treated by providers within each quartile of provider treatment intensity. Patient age at diagnosis, sex, comorbidity, and tumor grade did not vary according to the initial treatment intensity by the provider. Compared with providers in the lowest quartile of treatment intensity, those in the highest quartile of treatment intensity treated patients with slightly more severe bladder cancers, as evidenced by the higher proportion of their patients with high-grade (29.1% vs 28.5%, P  = .02) and stage T1 (28.6% vs 24.3%, P < .001) disease.
Table 1
Table 1
Patient and disease characteristics by provider treatment intensity*
As shown in Table 2, high–treatment intensity providers (ie, those in the highest quartile of treatment intensity) had higher rates of all surveillance- and treatment-related processes of care during the initial management of patients with early-stage bladder cancer than low–treatment intensity providers (ie, those in the lowest quartile of treatment intensity). Compared with patients who were treated by low–treatment intensity providers, those treated by high–treatment intensity providers were, on average, followed up more rigorously with bladder endoscopy (8.3 vs 7.3 procedures, P < .001), urine cytology (2.3 vs 1.3 tests, P < .001), and radiographic imaging (6.0 vs 5.1 studies, P < .001). Treatment-related processes of care followed similar trends. Patients who were treated by high–treatment intensity providers received statistically significantly more instillations (5.0 vs 2.6, P < .001) and induction courses (0.6 vs 0.5, P < .001) of intravesical therapy than patients who were treated by low–treatment intensity providers.
Table 2
Table 2
Provider practice styles according to average treatment intensity
Despite these differences in provider practice style, the median survival of patients was similar across all four quartiles of provider treatment intensity (Table 3) and ranged from 76.5 months for those whose providers were in the second highest quartile to 79.8 months for those whose providers were in the second lowest quartile (P = .50). Overall, 11 485 (55.4%) of the 20 713 patients died from any cause between January 1, 1992, and December 31, 2005. Patients treated by low–treatment intensity providers had a similar risk of death as those who were treated by high–treatment intensity providers (adjusted hazard ratio [HR] of death = 1.03, 95% confidence interval [CI] = 0.97 to 1.09) after adjusting for differences in demographics and cancer severity (ie, tumor grade and stage). When the patients were stratified by tumor grade and stage, we observed the anticipated effects of these markers of disease severity on survival, that is, patients with high-grade or T1 disease had generally lower survival than their counterparts with low-grade or Ta disease, respectively, at all levels of provider treatment intensity. However, as with the primary analysis, we observed no survival benefit associated with more intensive care. For example, among patients with T1 disease—a population with the highest risk of disease progression—those treated by low–treatment intensity providers had a similar risk of death as those treated by high–treatment intensity providers (adjusted HR of death = 0.98, 95% CI = 0.88 to 1.09).
Table 3
Table 3
All-cause and bladder cancer–specific mortality risks according to average provider treatment intensity*
Overall, 1613 (7.8%) patients died from bladder cancer between January 1, 1992, and December 31, 2005. However, as with the primary outcome, we observed no benefit of treatment intensity to bladder cancer–specific survival (Table 3). In fact, patients who were treated by low–treatment intensity providers had a 30% lower risk of death compared with those treated by high–treatment intensity providers (adjusted HR of death from bladder cancer = 0.70, 95% CI = 0.59 to 0.83). Similar relationships between treatment intensity and bladder cancer–specific survival were evident after stratifying patients by tumor grade and stage.
As shown in Figure 1, patients treated by high–treatment intensity providers were not less likely to require a subsequent major medical intervention than those treated by low–treatment intensity providers (11.0% vs 6.4%, P = .02). Indeed, patients treated by high–treatment intensity providers were more likely than patients treated by low–treatment intensity providers to undergo radical cystectomy, even after adjustment for differences between the two groups of patients (3.9% vs 1.6%, P < .001).
Figure 1
Figure 1
Use of major medical interventions among patients with early-stage bladder cancer by quartiles of provider treatment intensity, expressed as the percentage of patients adjusted for age, sex, race, comorbidity, socioeconomic status, and tumor grade and (more ...)
In a sensitivity analysis, we repeated the primary analysis by assessing treatment intensity and survival in separate patient populations. Briefly, treatment intensity was measured by use of providers' practice patterns for their patients diagnosed between January 1, 1992, and December 31, 1998. Overall mortality was then assessed for the same providers among their patients diagnosed with bladder cancer between January 1, 1999, and December 31, 2002. As with the primary analysis, we observed no differences in overall mortality according to treatment intensity (eg, adjusted HR of death for low vs high treatment intensity = 1.00, 95% CI = 0.89 to 1.13). A similar null relationship was observed when we used bladder cancer–specific survival as the outcome.
We found that urologists vary widely in the intensity of treatment they provide during the first 2 years after a diagnosis of early-stage bladder cancer. On average, providers in the highest quartile of treatment intensity had more than double the Medicare expenditures per patient compared with those in the lowest quartile. The high–treatment intensity style of practice was characterized by a greater use of all measured health services, including intravesical therapy, endoscopy, urinary studies, and imaging. However, this aggressive early treatment approach did not improve survival or prevent patients from having to undergo major medical interventions in subsequent years. In fact, compared with patients treated by low–treatment intensity urologists, those treated by high–treatment intensity urologists were nearly two and one-half times more likely to undergo radical cystectomy and nearly twice as likely to receive any major medical intervention, even after accounting for patient differences.
These findings highlight the lack of clinical consensus in how best to manage patients with early-stage bladder cancer. Current guidelines for the management of non–muscle-invasive bladder cancer generally favor the more intensive regimens of endoscopy and intravesical therapy (9). However, neither of these regimens has convincingly demonstrated the ability to prevent disease progression or to prolong patient survival (3234). Indeed, only one randomized trial (32) to our knowledge has explored the question of optimal endoscopic surveillance care. Because that study included only 97 patients, the findings were inconclusive. In light of the limited high-level evidence to guide clinical practice, the considerable variation in the early treatment of bladder cancer is not surprising.
One potential limitation of our analysis relates to unmeasured differences in patients among the physician treatment intensity groups. In particular, patients treated by high–treatment intensity urologists might have more aggressive disease than those treated by low–treatment intensity urologists, which could explain the apparent lack of benefit associated with treatment intensity. We addressed this well-described limitation of observational data (35,36) in several ways. First, we used a clinical registry to ascertain patients’ bladder cancer stage and grade, which are, arguably, the most important determinants of death in the bladder cancer patient population (7,37). Patients in the different treatment intensity groups were similar with respect to age, sex, and comorbidity. Second, we assessed treatment intensity at the level of the provider. Relative to a patient-level analysis, this approach is less susceptible to selection bias to the extent that it would require systematic variation in unmeasured risk factors across providers, which is probably less likely than variation in such risks across patients. Finally, our sensitivity analysis to assess treatment intensity and survival in separate patient populations also failed to demonstrate a survival advantage of more aggressive treatment.
Although more aggressive early treatment intensity was not associated with survival, it was associated with higher rates of major medical interventions, including radical cystectomy, systemic chemotherapy, and radiation therapy. There are several potential explanations for this finding. First, as discussed above, high–treatment intensity providers may have been treating sicker patients who, ultimately, required such interventions. However, unmeasured confounding seems unlikely given our approach of measuring treatment intensity at the level of the provider and the large differences in the rates of major intervention. Second, it is possible that more intensive therapy could, paradoxically, increase the risk of disease progression and thus the need for major medical interventions. However, we know of no biological mechanism to support this possibility. Third and perhaps most likely, provider practice styles with regard to the management of early-stage bladder cancer, as measured by their initial treatment intensity, may be consistent with those for more advanced disease. Simply put, urologists who treat aggressively early are likely to provide aggressive treatment in all aspects of bladder cancer care, and vice versa.
A second limitation of our findings relates to their applicability to the broader population of patients with early-stage bladder cancer. Because we relied on SEER–Medicare data, our findings may not be generalizable to patients younger than 65 years. However, it is important to note that nearly three-quarters of bladder cancer cases in the United States occur annually within the Medicare population (12). In early-stage bladder cancer, unlike in prostate cancer, treatment decisions generally are not made on the basis of the patient's age. Thus, extrapolation of our findings to the broader cohort (ie, all patients with early-stage bladder cancer) would appear to be reasonable. Although overall treatment intensity was not associated with better outcomes, it is possible that greater use of individual aspects of early-stage bladder cancer care (eg, endoscopic surveillance) could afford a benefit for some patients. Using observational data to identify such components of care may provide better and more efficient care in patients with early-stage bladder cancer. Finally, the lack of an association between treatment intensity and all-cause mortality among patients traditionally felt to be at high risk of disease progression (ie, those with stage T1 and/or high-grade tumors) does not preclude the possibility that some groups of patients may benefit from greater intensity of care; rather, it suggests that such patient populations are not readily identifiable by the grade and stage information captured in SEER.
Given the lack of association between treatment intensity and survival, our findings suggest the opportunity for reducing costs by eliminating unnecessary procedures and thus reducing wasteful spending for the care of patients with early-stage bladder cancer, which is already among the most expensive cancers in the United States (1). In light of the small but nontrivial risks associated with early-stage bladder cancer surveillance and treatment, the overuse of a high–treatment intensity practice style is worrisome given its lack of association with any benefit for the patients. Identifying best practices of care for patients diagnosed with early-stage bladder cancer must ultimately await the findings from future well-designed randomized clinical trials. In the meantime, urologists should not assume that more aggressive management of early-stage bladder cancer will translate into better outcomes for their patients.
Funding
American Cancer Society Pennsylvania Division—Dr. William and Rita Conrady Mentored Research Scholar Grant (MSRG-07-006-01-CPHPS to B.H.); American Urological Association Foundation (to B.H.); Astellas Pharma US, Inc. (to B.H.); National Cancer Institute (R01 CA098481-01A1, K05 CA115571-01 A2 to J.B.).
 
Appendix Table
Codes used to identify processes of care*
CategoryProcess of careVariable specificationICD-9 diagnosis codes (MEDPAR)HCPCS codes (National Claims History and Outpatient files)Descriptor
Surveillance relatedEndoscopic surveillanceDiscrete variable: use for each 1-month interval for 2 years after diagnosis (range = 0–24 months)57.32, 57.3952 000, 52 001, 52 005, 52 007Cystoscopy: with irrigation and evacuation of blood clots; with ureteral catheter; with brush biopsy of the ureter
57.3352 204, 52214Cystoscopy with biopsy, fulguration
52 250Cystoscopy with insertion of radioactive substance, with or without biopsy or fulguration
52 260, 52 265Cystoscopy with bladder dilation
57.9152 270, 52 275, 52 276, 52 277, 52 281, 52 282, 52 283, 52 285Cystoscopy with urethral dilation or urethrotomy
52 290, 52 300, 52 301, 52 305Cystoscopy with ureteral meatotomy
57.052 310, 52 315Cystoscopy with removal of foreign body
52 320, 52 325, 52 327, 52 330, 52 332, 52 334Cystoscopy for ureteral calculus
52 317, 52 318Cystoscopy with lithalopaxy
52 341, 52 342, 52 343Cystoscopy for ureteral stricture
57.92, 60.252 347, 52 400, 52 450, 52 500, 52 510, 52 601, 52 606, 52 612, 52 614, 52 620, 52 630, 52 640, 52 647, 52 648, 52 700Cystoscopy with transurethral prostate surgery
56.31, 56.3352 344, 52 345, 52 346, 52 351, 52 352, 52 353, 52 354, 52 355Cystoscopy with ureteroscopy
52 224Cystoscopy, with fulguration or treatment of minor (<0.5 cm) bladder lesions, with or without biopsy
57.4952 234, 52 235, 52 240Cystoscopy, with fulguration and/or resection of small (0.5 up to 2 cm), medium (2 up to 5 cm), large (≥5 cm) bladder tumors
Upper urinary tract evaluationDiscrete variable: use for each 1-month interval for 2 years after diagnosis (range 0–24)74 400, 74 410, 74 415Intravenous urography
74 420Retrograde urography
74 425Antegrade urography
74 150, 74 160, 74 170Abdominal CT
74 181, 74 182, 74 183, 74 185Abdominal MRI
Urinary studiesDiscrete variables: use (uniquely for urinalysis and cytology) for each 1-month interval for 2 years after diagnosis (range 0–24)81 000, 81 001, 81 002,  81 003, 81 005Urinalysis
Dichotomous variable: use of urine cytology at least once during 2-year interval
88 104, 88 106, 88 107, 88 108, 88 112, 88 160, 88 161, 88 162, 88 271, 88 272, 88 273, 88 274, 88 275, 88 291Urine cytology and cytogenetics
Imaging studiesContinuous variable: number of unique claims over 2-year interval71 010, 71 015, 71 020, 71 021, 71 022, 71 023, 71 030, 71 034, 71 035Chest radiography
71 250, 71 260, 71 270, 71 275Chest CT
71 550, 71 551, 71 552, 71 555Chest MRI
74 150, 74 160, 74 170Abdominal CT
74 181, 74 182, 74 183, 74 185Abdominal MRI
72 191, 72 192, 72 193, 72 194Pelvis CT
72 195, 72 196, 72 197Pelvis MRI
76 497Unlisted CT
76 498Unlisted MRI
78 810PET scan
74 400, 74 410, 74 415Intravenous urography
74 420Retrograde urography
74 425Antegrade urography
76 700, 76 770, 76 705, 76 775, 76 778Abdominal or renal ultrasound
78 700, 78 701, 78 704, 78 707, 78 708, 78 709, 78 715Nuclear medicine renal scan
78 300, 78 305, 78 306, 78 315, 78 320Nuclear medicine bone scan
78 800, 78 801, 78 802, 78 990Radiopharmaceutical localization of tumor or distribution of radiopharmaceutical agents
Treatment relatedIntravesical therapyContinuous variables: number of unique claims over 2-year interval; and, measure number of induction courses over 2-year interval51 720Bladder instillation of anticarcinogenic agent
Dichotomous variable: use of induction chemotherapy at least once during 2-year interval
51 700Bladder irrigation, with or without instillation
51 701Insertion of a nonindwelling catheter
51 702, 51 703Insertion of a temporary indwelling catheter
J8520, J8521Capecitabine
J9000, J9001Doxorubicin
J9031Intravesical Bacille Calmette-Guérin
J9201Gemcitabine
J9280, J9290, J9291Mitomycin
J9340Thiotepa
Repeat endoscopic resectionDichotomous variable: use of repeat endoscopic resection within 60 days of initial resection or biopsy57.4952 234, 52 235, 52 240Cystoscopy, with fulguration and/or resection of small (0.5 up to 2 cm); medium (2 up to 5 cm); large (≥5 cm) tumors
Medical servicesVisits to the urologistContinuous variable: number of unique claims over 2-year interval99 201–99 205New patient, outpatient
99 211–99 215Established patient, outpatient
99 218–99 220, 99 234–99 236Initial, established, observation unit
99 221–99 223Initial, inpatient
99 231–99 233Subsequent, inpatient
99 241–99 245Consult, outpatient
99 251–99 255Consult, inpatient, new
99 261–99 263Consult, inpatient, established
99 271–99 275Confirmatory consult
Visits to other physiciansContinuous variable: number of unique claims over 2-year interval99 201–99 205New patient, outpatient
99 211–99 215Established patient, outpatient
99 218–99 220, 99 234–99 236Initial, established, observation unit
99 221–99 223Initial, inpatient
99 231–99 233Subsequent, inpatient
99 241–99 245Consult, outpatient
99 251–99 255Consult, inpatient, new
99 261–99 263Consult, inpatient, established
99 271–99 275Confirmatory consult
*ICD-9 = International Classification of Diseases, 9th Revision; MEDPAR = Medicare Provider Analysis and Review file; HCPCS = Healthcare Common Procedure Coding System; CT = computed tomography; MRI = magnetic resonance imaging; PET = positron emission tomography.
Induction intravesical therapy: at least five unique claims for instillation of any anticarcinogenic agent within a 45-day period.
Footnotes
The study sponsors had no role in the design of the study; the collection, analysis, or interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication.
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