| Literature DB >> 32203532 |
Michael E Rezaee1,2, Kristine E Lynch3, Zhongze Li4, Todd A MacKenzie4,5, John D Seigne1,6, Douglas J Robertson1,5, Brenda Sirovich1,5, Philip P Goodney1,5, Florian R Schroeck1,2,5,6.
Abstract
PURPOSE: To assess the association of low- vs. guideline-recommended high-intensity cystoscopic surveillance with outcomes among patients with high-risk non-muscle invasive bladder cancer (NMIBC). MATERIALS &Entities:
Mesh:
Year: 2020 PMID: 32203532 PMCID: PMC7089561 DOI: 10.1371/journal.pone.0230417
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Categorizing patients into low versus high-intensity surveillance based on consensus guideline recommendations and length of the surveillance window.
[3] At the top of the figure, the timeline of the surveillance window is depicted in months. X denotes the recommended time of cystoscopy. A 1.5 month grace period was allotted to allow for surveillance cystoscopies that were done slightly later than recommended. For example, a patient followed for 9.5 months (second column) who underwent 0 or 1 cystoscopies was categorized as low-intensity surveillance, whereas a patient followed for 9.5 months who underwent 2 or more cystoscopies was categorized as high-intensity surveillance. In the table, the number of patients categorized into low versus high-intensity surveillance (overall and stratified by length of surveillance window), and number of surveillance cystoscopies is depicted.
Baseline patient characteristics of 1,542 patients diagnosed with high-risk NMIBC stratified by low versus-high intesity cystoscopic surveillance.
| Total / All patients (n = 1542) | High intensity surveillance (n = 1022) | Low intensity surveillance (n = 520) | P-value | |
|---|---|---|---|---|
| Age (median, IQR) | 77 (66–95) | 76 (66–95) | 77 (66–94) | 0.04 |
| Age ≥80 (N, %) | 555 (36) | 343 (33.6) | 212 (40.8) | <0.01 |
| Male Sex (N, %) | >1531 (>99.2) | >1011 (>98.9) | >509 (>97.8) | 0.33 |
| Race (N, %) | ||||
| White | >1273 (>82.5) | >856 (>83.7) | 414 (79.6) | 0.04 |
| Black | 113 (7.3) | 60 (5.9) | 53 (10.2) | |
| Asian | 14 (0.9) | 11 (1.1) | <11 (<2.2) | |
| Hispanic | 23 (1.5) | 16 (1.6) | <11 (<2.2) | |
| Native American | <11 (<0.8) | <11 (<1.1) | <11 (<2.2) | |
| Unknown | 108 (7) | 68 (6.7) | 40 (7.7) | |
| Comorbidity (N, %) | ||||
| 0 | 226 (14.7) | 142 (13.9) | 84 (16.2) | 0.39 |
| 1 | 403 (26.1) | 273 (26.7) | 130 (25) | |
| 2 | 404 (26.2) | 277 (27.1) | 127 (24.4) | |
| ≥3 | 509 (33) | 330 (32.3) | 179 (34.4) | |
| Nosos-p score | 1.6 (0.4–7.5) | 1.7 (0.5–7.5) | 1.5 (0.4–7.3) | 0.01 |
| Year of diagnosis (N, %) | ||||
| 2005 | 33 (2.1) | 20 (2) | 13 (2.5) | 0.33 |
| 2006 | 182 (11.8) | 121 (11.8) | 61 (11.7) | |
| 2007 | 222 (14.4) | 140 (13.7) | 82 (15.8) | |
| 2008 | 267 (17.3) | 164 (16) | 103 (19.8) | |
| 2009 | 269 (17.4) | 184 (18) | 85 (16.3) | |
| 2010 | 312 (20.2) | 215 (21) | 97 (18.7) | |
| 2011 | 257 (16.7) | 178 (17.4) | 79 (15.2) | |
| Proportion living in ZIP code with ≥25% college graduates (N, %) | 645 (41.8) | 436 (42.7) | 209 (40.2) | 0.35 |
| Living in urban vs. rural area (N, %) | ||||
| Urban | 929 (60.2) | 608 (59.5) | 321 (61.7) | 0.40 |
| Rural | 613 (39.8) | 414 (40.5) | 199 (38.3) | |
| Stage | ||||
| Ta (high grade or associated with carcinoma in situ) | 599 (38.8) | 404 (39.5) | 195 (37.5) | 0.69 |
| T1 | 872 (56.5) | 570 (55.8) | 302 (58.1) | |
| Carcinoma in situ only | 71 (4.6) | 48 (4.7) | 23 (4.4) | |
| Carcinoma in situ | 330 (21.4) | 227 (22.2) | 103 (19.8) | 0.28 |
| Bladder Cancer Grade | ||||
| Low | 196 (12.7) | 123 (12) | 73 (14) | 0.26 |
| High | 1346 (87.3) | 899 (88) | 447 (86) | |
| Intravesical Therapy (N,%) | 859 (56) | 597 (58) | 262 (50) | <0.01 |
* From Chi-square test for categorical variable and Wilcoxon test for continuous variables whose median and IQR were presented. Missing observations were excluded for analysis.
** Exact numbers not shown to protect confidentiality.
*** The Nosos-p score is a risk-adjustment score based on diagnosis codes, biographic information (including gender, date of birth, insurance coverage, race, marital status, VA priority (priority 1–9), and inclusion in a VA registry), drug prescription data and utilization costs. The “-p” indicates it is a prospective score, using data from one fiscal year to predict future health care utilization in the next fiscal year.
**** Low-grade tumors were only included if they were T1 or associated with carcinoma in situ.
***** Not included in initial propensity score adjustment. However, all Fine-Gray models were adjusted for receipt on intravesical chemotherapy.
Fig 3Cumulative incidence plots showing the probability of 1) bladder cancer death by Ta versus T1 disease and by cystoscopic surveillance intensity (Panel A) and 2) progression to invasive disease (T1 or T2) or bladder cancer death among those with Ta disease (Panel B). Data are from Fine and Gray competing risk models adjusted for propensity score and receipt of intravesical therapy with death from other causes modeled as a competing risk.
Fig 2Sensitivity analyses, now including any patients who died or had their last contact with the VA health system during the first two years after diagnosis.
Cumulative incidence plots showing the probability of 1) bladder cancer death by Ta versus T1 disease and by cystoscopic surveillance intensity (Panel A) and 2) progression to invasive disease (T1 or T2) or bladder cancer death among those with Ta disease (Panel B). Data are from Fine and Gray competing risk models adjusted for propensity score and receipt of intravesical therapy with death from other causes modeled as a competing risk.
Fig 4Number of total transurethral resctions and resections with cancer in the pathology specimen by low versus high-intensity surveillance.
Patients who underwent low-intensity surveillance experienced 3-times fewer total transurethral resections and resection with cancer in the specimen compared to high-intensity surveillance patients.