A hospital-based study of initial observation for low-risk prostate cancer and its predictors in the United States.
The overdiagnosis and overtreatment of prostate cancer has become a national public health concern. (1) Early prostate cancer detection through widespread prostate-specific antigen (PSA) screening reduces cancer-specific mortality and the incidence of metastatic disease in a small proportion of men at the expense of exposing many more men to its associated risks. (2,3) Early detection with PSA screening over-diagnoses 23% to 42% of prostate cancer, leading to over-treatment and its related harms. (4-6) Citing this unfavourable risk-benefit ratio, the United States Preventative Services Task Force (USPSTF) recommended against screening in all men. (1) While a ban on screening would eliminate overdiagnosis entirely, it also would permit 3000 to 4000 avoidable prostate cancer deaths annually. (7) An alternative solution to overtreatment is to restrict screening to age-appropriate men and to limit treatment based on patient life expectancy and disease characteristics.
Watchful waiting (WW) and active surveillance (AS) minimize overtreatment by avoiding or delaying curative treatment in well-selected men, respectively. Both strategies involve a period of initial observation (IO) followed either by continued observation in elderly or sickly men who are unlikely to benefit from active treatment (WW) or by active monitoring with selective delayed intervention in men at higher risk for disease progression (AS). It is now clear that neither strategy sacrifices short-term cancer-specific survival in men with low-risk disease. (8-11) Seemingly, the primary barrier limiting the effectiveness of IO to combat overtreatment in this country has been its acceptance by urologists. (12)
Historically IO has been used at very low rates in the United States, largely relegated to use in older men. (13,14) With the introduction of AS in 2002, IO became a feasible option for all men with low-risk prostate cancer. (15) While recent IO usage appears to be robust in Scandinavia, little is known about its contemporary uptake in the United States or the factors that influence its utilization. (11,16) We sought to examine IO utilization and its predictors in a national sample of men using the National Cancer Database (NCDB).
The NCDB, a joint project of the American Cancer Society and the Commission on Cancer (CoC) of the American College of Surgeons, is a comprehensive clinical oncology dataset that captures 70% of all incident malignancies in the United States. It has been validated previously against the SEER (Surveillance, Epidemiology and End Results) database. (17) The dataset contains only de-identified data, obviating the need for institutional review board approval.
We identified 1 666 913 patients with histologically confirmed prostate cancer based on ICD-O-3 primary site (C619) and histology (8140) codes. The study period was limited to diagnosis years 2004 to 2011 because PSA data were not available prior to 2004 (n = 973 558). Only patients with prostate cancer as their sole or first cancer diagnosis were included to avoid confounding from prior cancer treatments (n = 900 580). We limited our cohort to men with low-risk prostate cancer by the D'Amico criteria, defined as Gleason score <6 (no Gleason pattern 4 or 5), TNM clinical T stage T1-T2a, and PSA <10 (n = 220 187). After excluding nodal and metastatic disease, 219 971 patients were available for analysis.
The NCDB only includes data on "first course of treatment," defined as all methods of treatment recorded in the treatment plan and administered to the patient before disease progression or recurrence. IO was defined as no first course treatment. Active treatment included prostatectomy, radiation therapy, androgen deprivation, and other unspecified treatments (which accounted for <3% of cases). To identify factors associated with IO utilization for low-risk prostate cancer, we compared men who underwent IO to those who received active treatment.
Univariate analysis was performed using the Pearson chi-square test. For multivariate logistic regression, adjusted odds ratios were calculated with IO as the response variable and diagnosis year, race, residence, education, income, insurance, age, comorbidity, hospital type, and hospital location as covariates. Statistical tests were performed using SAS version 9.3 (SAS Institute Inc., Cary, NC). P values <0.01 were considered statistically significant.
Overall, from 2004-2011, 9.7% (21 231/219 971) of men with low-risk prostate cancer were managed with IO, while 198,740 were actively treated. The low-risk prostate cancer population was composed of predominantly more educated, wealthier, insured Caucasian men living in metropolitan areas who sought care at major academic and comprehensive cancer centers throughout the United States (Table 1). Patients were primarily healthy and younger than age 70. Most men had clinical T1c prostate cancer and PSA >4.
Diagnosis year was one of the strongest determinants of receiving IO. From 2004 to 2007, IO utilization remained relatively stable (range: 7.2-7.5%). Beginning in 2008, IO usage rose steadily, peaking at 14.3% by 2011 (Fig. 1). Compared to 2004, patients diagnosed in 2011 had 2.5 times the odds of receiving IO (odds ratio [OR] 2.5, confidence interval [CI] 2.3-2.6, p < 0.01).
Aside from diagnosis year, clinical factors were also significant predictors of IO usage (Table 2). In particular, age was the single greatest predictor of IO utilization. Compared to patients <50 years, patients >70 years had 2.5 times the odds of receiving IO (OR 2.5, CI 2.3-2.7, p < 0.01) and those >80 years had 7.2 times greater odds (OR 7.2, CI 6.4-8.0, p < 0.01). Charlson comorbidity index (CCI) had a small, but significant, impact on IO utilization as well. Patients with more than one comorbidity had 10% increased odds of receiving IO than those without comorbidities (p < 0.01). Men with PSA >4 or clinical T2 disease were significantly less likely (10% and 30% decreased odds, respectively) of undergoing IO than those with T1 disease or PSA <4 (p < 0.01).
Albeit to a lesser extent, demographic factors were also important predictors of IO usage. African American and other, non-Hispanic minority men had 20% and 30% increased odds of receiving IO compared to Caucasian men (OR 1.2, CI 1.2-1.3; OR 1.3, CI 1.2-1.4; p < 0.01, respectively). Less educated men and wealthier men were both significantly less likely to receive IO (OR 0.8, CI 0.8-0.9; OR 0.8, CI 0.8-0.9; p < 0.01, respectively).
Non-clinical factors that significantly predicted IO use included: insurance provider, hospital type, and, to a lesser degree, hospital region. IO usage was highest in the uninsured and in patients with social insurance. Compared to patients with private insurance, patients with social insurance had 1.2 times the odds of receiving IO (OR 1.2, CI 1.2-1.3, p < 0.01), while uninsured patients had 2.5 times the odds (OR 2.5, CI 2.3-2.8, p < 0.01). IO was most frequently utilized at academic centres. Men treated at academic centres had 2.1, 1.2, and 1.9 times the odds of receiving IO compared to patients treated at comprehensive centres, community cancer programs, and other hospitals, respectively (p < 0.01). IO was most common in western United States, followed by the northeast, south, and midwest regions (p < 0.01) (See Appendix). Within a particular region, IO selection did not significantly depend on the patient's place of residence (rural, urban, or metropolitan, using the typology published by the United States Department of Agriculture Economic Research Service). (18)
From 2007 onward, IO usage increased gradually at a rate of 1.7% per year, peaking at 14.3%. This rise may be related to greater acceptance of AS, which was first included in clinical practice guidelines as an alternative to active treatment in 2007. (19) In general, however, IO use was higher in men with limited life expectancies (age >70 and CCI [greater than or equal to] 2), suggesting WW-predominant practice patterns. (20) This is a change from pre-2008 trends, in which aggressive treatment was administered regardless of patient life expectancy. (21) We found that academic centres in the United States led the way in IO adoption. Interestingly, men receiving IO were more likely to be poor or belong to a minority group and were less likely to have private health insurance than their counterparts.
While our study is one of the first to demonstrate the more recent rise in IO utilization in the United States, our baseline IO rate (7.4%) from 2004 to 2007 is consistent with prior research. Cooperberg and colleagues reported an 8.5% utilization rate of observation for low-risk prostate cancer from 2004 to 2007, using the CaPSURE database. (22) On the contrary, Ritch and colleagues recently reported a much higher and rising rate of observation (from 18% in 2004 to 29% in 2009) in men with low-risk disease; however, since their data only included men age 65 and older, these results may have been influenced by selection bias. (23) Loeb and colleagues also noted increasing AS utilization in Sweden over the same interval (2007-201 1). (16) However, AS rates for low- and very low-risk disease in Sweden were much higher (41%-59%) than our IO rates, possibly reflecting both cultural and financial disparities in practice patterns between the United States and Scandinavia. (16)
It is estimated that 38% to 60% of patients diagnosed with early prostate cancer are considered low risk by D'Amico criteria and thus are candidates for management with IO. (11,24) Based on these estimates, our findings suggest that IO is still being underutilized in the United States despite its recent gains. The reasons behind underutilization are likely multifactorial.
The lack of clear recommendations favouring AS may have contributed to IO underutilization. For most of the diagnosis period (2004-2007), AS was not an accepted strategy for low-risk prostate cancer. (18) Also, preliminary results from the largest prospective AS cohort (Prostate Cancer Research International: Active Surveillance, PRIAS), were not available until 2009.25 Moreover, the limited benefit of active treatment for low-risk, screen-detected prostate cancer was not yet known. (8) Consequently, community urologists may have considered AS experimental, explaining why academic centres were primarily responsible for the rise in IO use.
Racial/ethnic and socioeconomic disparities in treatment selection for prostate cancer are well-recognized. It has been shown that African-American men are more likely to be managed expectantly than white men. (26) Similarly, poor men and men with public health insurance are more likely to be treated conservatively. (27,28) In keeping with these disparities, we found that minority men, especially African-Americans, men from lower socioeconomic groups, and uninsured or socially insured men preferentially received IO. While increased IO utilization as a whole should be considered an achievement, its preferential use in certain racial and socioeconomic groups is not evidence-based and may be detrimental. In particular, African-American men, who have a higher disease progression rate on AS, may not be the best candidates for this approach. (29) Furthermore, poor men may experience inferior outcomes when managed conservatively. (28)
It is unclear why poor and uninsured or underinsured men were more inclined to receive IO. This disparity does not appear to be caused by local differences in resource availability, since area of residence did not affect IO selection. Given that IO is associated with lower upfront costs than active treatments, it is possible that financial considerations influenced treatment decisions. (30) This also may explain why non-academic/non-research hospitals, which rely on fee-for-service reimbursement, preferentially utilized higher-cost treatments. In contrast, at government-sponsored Veterans Affairs hospitals, which are less influenced by reimbursement concerns, IO utilization is higher. (31)
There are significant barriers to widespread AS adoption in the United States. While patient anxieties may limit utilization, physician influence is the single most important factor influencing the decision to undergo AS. (12,32) Interestingly, we found that education level was associated with treatment selection, with educated men more likely to choose IO. Men with poor prostate cancer knowledge have more decisional conflict and decision-making impairment than educated men, potentially explaining their reluctance to pursue AS. (33) Urologists must promote AS, educating and reassuring low-risk patients on the benefits of IO relative to active treatment.
A clear strength of our study is the NCDB's comprehensiveness, capturing over 70% of incident cancers in the United States regardless of age. Since hospitals included in the NCDB exhibit higher levels of cancer specialization than other hospitals, our findings may demonstrate the best-case scenario in terms of contemporary IO utilization.
The main limitation of this study is its retrospective nature. Since the NCDB does not code IO as a unique treatment, we used lack of treatment to define IO. This definition is somewhat flawed because treatment delay may be erroneously construed as IO, leading to misclassification and overestimation of the IO rate. Fortunately, the NCBD makes every effort to assign treatments appropriately to minimize this error. Similarly, the NCDB does not differentiate AS from WW, nor does it include data on number of positive cores, re-biopsies or second-course treatments, limiting our ability to selectively identify AS patients.
IO has been utilized increasingly for low-risk prostate cancer in the United States, especially in patients least likely to benefit from active treatment. Despite this progress, IO is still underutilized, possibly due to the influence of non-clinical factors. The future of AS and, for that matter, of prostate cancer diagnosis depends on the continued adoption of IO by urologists.
Acknowledgements: An abstract of the work was presented at the American Society of Clinical Oncology Genitourinary Cancers Symposium in San Francisco, CA on January 30, 201 4 and at the American Urological Association annual meeting in Orlando, FL on May 20, 201 4. The American College of Surgeons and the Commission on Cancer have not verified and are not responsible for the analytic or statistical methodology employed, or the conclusions drawn from these data by the investigator.
Competing interests: The authors declare no competing financial or personal interests.
This paper has been peer-reviewed.
(1.) Moyer VA, U.S. Preventive Services Task Force. Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2012;157:120-34. http://dx.doi. org/10.7326/0003-4819-157-2-201207170-00459
(2.) Schroder FH, Hugosson J, Roobol MJ, et al. Screening and prostate cancer mortality: Results of the European Randomised Study of Screening for Prostate Cancer (ERSPC) at 13 years of follow-up. Lancet 2014;384:2027-35. http://dx.doi.org/10.1016/S0140-6736(14)60525-0. Epub 2014 Aug 6.
(3.) Hugosson J, Carlsson S, Aus G, et al. Mortality results from the Goteborg randomised population-based prostate-cancer screening trial. Lancet Oncol 2010;11:725-32. http://dx.doi.org/10.1016/S14702045(10)70146-7
(4.) Draisma G, Etzioni R, Tsodikov A, et al. Lead time and overdiagnosis in prostate-specific antigen screening: Importance of methods and context. J Natl Cancer Inst 2009;101:374-83. http://dx.doi.org/10.1093/ jnci/djp001
(5.) Sandhu GS, Andriole GL. Overdiagnosis of prostate cancer. J Natl Cancer InstMonogr 2012;2012:146-51.
(6.) Resnick MJ, Koyama T, Fan KH, et al. Long-term functional outcomes after treatment for localized prostate cancer. N Engl J Med 2013;368:436-45. http://dx.doi.org/10.1056/NEJMoa1209978
(7.) Gulati R, Tsodikov A, Etzioni R, et al. Expected population impacts of discontinued prostate-specific antigen screening. Cancer 2014;120:3519-26. http://dx.doi.org/10.1002/cncr.28932
(8.) Wilt TJ, Brawer MK, Jones KM, et al. Radical prostatectomy versus observation for localized prostate cancer. N Engl J Med 2012;367:203-13. http://dx.doi.org/10.1056/NEJMoa1113162
(9.) Klotz L, Zhang L, Lam A, et al. Clinical results of long-term follow-up of a large, active surveillance cohort with localized prostate cancer. J Clin Oncol 2010;28:126-31. http://dx.doi.org/10.1200/ JCO.2009.24.2180
(10.) Bul M, van den Bergh RC, Zhu X, et al. Outcomes of initially expectantly managed patients with low or intermediate risk screen-detected localized prostate cancer. BJU Int 2012;110:1672-7. http://dx.doi. org/10.1111/j.1464-410X.2012.11434.x
(11.) Godtman RA, Holmberg E, Khatami A, et al. Outcome following active surveillance of men with screen-detected prostate cancer. Results from the Goteborg randomised population-based prostate cancer screening trial. Eur Urol 2013;63:101-7. http://dx.doi.org/10.10167j.eururo.2012.08.066
(12.) Davison BJ, Breckon E. Factors influencing treatment decision making and information preferences of prostate cancer patients on active surveillance. Patient Educ Corns 2012;87:369-74. http://dx.doi. org/10.1016/j.pec.2011.11.009
(13.) Cooperberg MR, Lubeck DP, Meng MV, et al. The changing face of low-risk prostate cancer: Trends in clinical presentation and primary management. J Clin Oncol 2004;22:2141-9. http://dx.doi.org/10.1200/ JCO.2004.10.062
(14.) Wu H, Sun L, Moul JW, et al. Watchful waiting and factors predictive of secondary treatment of localized prostate cancer. J Urol 2004;171:1111-6. http://dx.doi.org/10.1097/01.ju.00001 13300.74132.8b
(15.) Choo R, Klotz L, Danjoux C, et al. Feasibility study: Watchful waiting for localized low to intermediate grade prostate carcinoma with selective delayed intervention based on prostate specific antigen, histological and/or clinical progression. J Urol 2002;167:1664-9. http://dx.doi.org/10.1016/S00225347(05)65174-9
(16.) Loeb S, Berglund A, Stattin P. Population-based study of utilization and determinants of active surveillance and watchful waiting for low- and intermediate-risk prostate cancer. J Urol 2013;190:1742-9. http:// dx.doi.org/10.1016/j.juro.2013.05.054
(17.) Mettlin CJ, Menck HR, Winchester DP, et al. A comparison of breast, colorectal, lung, and prostate cancers reported to the National Cancer Data Base and the Surveillance, Epidemiology, and End Results Program. Cancer 1 997;79:2052-61. http://dx.doi.org/10.1002/ (SICI)10970142(19970515)79:10<2052::AID-CNCR29>3.0.C0;2-S
(18.) United States Department of Agriculture Economic Research Service; 2003. http://www.ers.usda.gov/ data-products/rural-urban-continuum-codes. Accessed April 13, 2015.
(19.) Thompson I, Thrasher JB, Aus G, et al. Guideline for the management of clinically localized prostate cancer: 2007 update. J Urol 2012;177:2106-31. http://dx.doi.org/10.1016/jduro.2007.03.003
(20.) Vickers A, Bennette C, Steineck G, et al. Individualized estimation of the benefit of radical prostatectomy from the Scandinavian Prostate Cancer Group randomized trial. Eur Urol 2012;62:204-9. http://dx.doi. org/10.1016/j.eururo.2012.04.024
(21.) Daskivich TJ, Lai J, Dick AW, et al. Variation in treatment associated with life expectancy in a population-based cohort of men with early-stage prostate cancer. Cancer 2014;1 20:3642-50. http://dx.doi. org/10.1002/cncr.28926
(22.) Cooperberg MR, Broering JM, Carroll PR. Time trends and local variation in primary treatment of localized prostate cancer. J Ciin Oncol 2010;28:11 17-23. http://dx.doi.org/10.1200/JC0.2009.26.0133
(23.) Ritch CR, Graves AJ, Keegan KA, et al. Increasing use of observation among men at low risk for prostate cancer mortality. J Urol 2015;193:801-6. http://dx.doi.org/10.1016/jduro.2014.08.102. Epub 2014 Sep 6.
(24.) Barocas DA, Cowan JE, Smith JA, Jr, et al. What percentage of patients with newly diagnosed carcinoma of the prostate are candidates for surveillance? An analysis of the CaPSURE database. J Urol 2008;180:13305. http://dx.doi.org/10.1016/jduro.2008.06.019
(25.) van den Bergh RC, Vasarainen H, van der Poel HG, et al. Short-term outcomes of the prospective multicentre 'Prostate Cancer Research International: Active Surveillance' study. BJU Int 2010;105:956-62. http:// dx.doi.org/10.1111/j.1464-410X.2009.08887.x
(26.) Underwood W, De Monner S, Ubel P, et al. Racial/ethnic disparities in the treatment of localized/regional prostate cancer. J Urol 2004;171:1504-7. http://dx.doi.org/10.1097/01.ju.0000118907.64125.e0
(27.) Schymura MJ, Kahn AR, German RR, et al. Factors associated with initial treatment and survival for clinically localized prostate cancer: Results from the CDC-NPCR Patterns of Care Study (PoC1). BMC Cancer 2010;10:1-15. http://dx.doi.org/10.1 186/1471-2407-10-152
(28.) Aarts MJ, Koldewijn EL, Poortmans PM, et al. The impact of socioeconomic status on prostate cancer treatment and survival in the southern Netherlands. Urology 2013;81:593-9. http://dx.doi.org/10.1016/j. urology.2012.11.011
(29.) Odom BD, Mir MC, Hughes S, et al. Active surveillance for low-risk prostate cancer in African American men: A multi-institutional experience. Urology 2014;83:364-8. http://dx.doi.org/10.1016/j.urology.2013.09.038
(30.) Corcoran AT, Peele PB, Benoit RM. Cost comparison between watchful waiting with active surveillance and active treatment of clinically localized prostate cancer. Urology 2010;76:703-7. http://dx.doi. org/10.1016/j.urology.2009.12.071
(31.) Maurice MJ, Abouassaly R, Zhu H. American trends in expectant management utilization for prostate cancer from 2000-2009. Can Urol Assoc J 2014;8:E775-82. http://dx.doi.org/10.5489/cuaj.2073
(32.) Gorin MA, Soloway CT, Eldefrawy A. Factors that influence patient enrollment in active surveillance for low-risk prostate cancer. Urology 2011;77:588-91. http://dx.doi.org/10.1016/j.urology.2010.10.039
(33.) Kaplan AL, Crespi CM, Saucedo JD, et al. Decisional conflict in economically disadvantaged men with newly diagnosed prostate cancer: Baseline results from a shared decision-making trial. Cancer 2014;120:2721-7. http://dx.doi.org/10.1002/cncr.28755
Correspondence: Dr. Robert Abouassaly, University Hospitals Case Medical Center, Cleveland, OH; firstname.lastname@example.org
Appendix 1. Regions and their corresponding states Region State/District Northeast Connecticut Maine Massachusetts New Hampshire New Jersey New York Pennsylvania Rhode Island Vermont Midwest Illinois Indiana Iowa Kansas Michigan Minnesota Missouri Nebraska North Dakota Ohio South Dakota Wisconsin South Alabama Arkansas Delaware Florida Georgia Kentucky Louisiana Maryland Mississippi North Carolina Oklahoma South Carolina Tennessee Texas Virginia Washington, D.C. West Virginia West Alaska Arizona California Colorado Hawaii Idaho Montana Nevada New Mexico Oregon Utah Washington Wyoming
Matthew J. Maurice, MD;* Hui Zhu, MD([dagger]) Robert Abouassaly, MD*
University Hospitals Case Medical Center, Cleveland, OH; ([dagger]) Louis Stokes Cleveland VA Medical Center and Cleveland Clinic South Pointe Hospital, Cleveland, OH
Published online April 13 2015.
Caption: Fig. 1. Initial observation utilization for low-risk prostate cancer.
Table 1. Characteristics of men with low-risk prostate cancer managed with initial observation vs. active treatment IO % T % Race Non-Hispanic white 16 262 76.6 160 041 80.5 Hispanic 789 3.7 6429 3.2 African-American 2885 13.6 23 378 11.8 Other minority 1295 6.1 8892 4.5 Patient residence Metropolitan 16 896 82.9 154 550 81.7 Rural 417 2.0 4427 2.3 Urban 3073 15.1 30 224 16.0 Education level Lowest 2943 14.5 25 902 13.7 Lower middle 4015 19.8 39 967 21.2 Upper middle 4575 22.6 45 428 23.9 Highest 8752 43.1 78 454 41.3 Income level Lowest 2500 12.3 21 440 11.3 Lower middle 3392 16.7 31 048 16.4 Upper middle 5341 26.3 51 491 27.1 Highest 9054 44.6 85 786 45.2 Insurance Private 9244 81.4 110 638 56.5 Uninsured 489 2.4 2201 1.1 Federal/social 10 867 52.8 82 844 42.3 Age, years <50 656 3.1 9249 4.7 50-59 4487 21.1 57 948 29.2 60-69 8680 40.9 86 371 43.5 70-79 6168 29.1 41 894 21.1 >80 1240 5.8 3278 1.6 Charlson score 0 18 978 89.4 173 227 87.2 1 1828 8.6 22 429 11.3 >1 425 2.0 3084 1.6 Clinical T stage T1a 985 4.6 3698 1.9 T1b 251 1.2 1305 0.7 T1c 17 972 84.6 169 171 85.1 T2a 2023 9.5 24 566 12.4 PSA <4 5072 23.9 46 818 23.6 4-10 16 159 76.1 151 922 76.4 Hospital type Academic 10 652 50.2 71 332 35.9 Community 2100 9.9 16 122 8.1 Comprehensive 8349 39.3 109 727 55.2 Other 130 0.6 1559 0.8 Hospital location Midwest 5017 23.6 50 323 25.3 Northwest 5481 25.8 45 897 23.1 South 6958 32.8 70 341 35.4 West 3775 17.8 32 179 16.2 Total % p value * Race <0.01 Non-Hispanic white 176 303 80.1 Hispanic 7218 3.3 African-American 26 263 11.9 Other minority 10 187 4.6 Patient residence <0.01 Metropolitan 171 446 81.8 Rural 4844 2.3 Urban 33 297 15.9 Education level <0.01 Lowest 28 845 13.7 Lower middle 43 982 20.9 Upper middle 50 003 23.8 Highest 87 206 41.5 Income level <0.01 Lowest 23 940 11.4 Lower middle 34 440 16.4 Upper middle 56 832 27.1 Highest 94 840 45.2 Insurance <0.01 Private 119 882 55.4 Uninsured 2690 1.2 Federal/social 93 711 43.3 Age, years <0.01 <50 9905 4.5 50-59 62 435 28.4 60-69 95 051 43.2 70-79 48 062 21.8 >80 4518 2.1 Charlson score <0.01 0 192 205 87.4 1 24 257 11.0 >1 3509 1.6 Clinical T stage <0.01 T1a 4683 2.1 T1b 1556 0.7 T1c 187 143 85.1 T2a 26 589 12.1 PSA 0.11 <4 51 890 23.6 4-10 168 081 76.4 Hospital type <0.01 Academic 81 984 37.3 Community 18 222 8.3 Comprehensive 118 076 53.7 Other 1689 0.8 Hospital location <0.01 Midwest 55 340 25.2 Northwest 51 378 23.4 South 77 299 35.1 West 35 954 16.3 * p values <0.01 considered significant. IO: initial observation; T: active treatment; PSA: prostate-specific antigen. Table 2. Multivariate logistic regression analysis of predictors of initial observation utilization Variable Adjusted OR 95% CI p value * Diagnosis year <0.01 2004 1.0 (referent) 2005 1.0 1.0-1.1 2006 1.1 1.0-1.1 2007 1.1 1.0-1.2 2008 1.4 1.3-1.5 2009 1.9 1.8-2.0 2010 2.0 1.9-2.1 2011 2.5 2.3-2.6 Race <0.01 Non-Hispanic white 1.0 (referent) Hispanic 1.1 1.0-1.2 African-American 1.2 1.2-1.3 Other 1.3 1.2-1.4 Patient residence 0.10 Metropolitan 1.0 (referent) Rural 0.9 0.8-1.0 Urban 1.0 0.9-1.0 Education level <0.01 Highest 1.0 (referent) Upper middle 0.9 0.8-0.9 Lower middle 0.8 0.8-0.8 Lowest 0.8 0.8-0.9 Income level <0.01 Lowest 1.0 (referent) Lower middle 1.0 0.9-1.1 Upper middle 0.9 0.9-1.0 Highest 0.8 0.8-0.9 Insurance <0.01 Private 1.0 (referent) Federal/social 1.2 1.2-1.3 Uninsured 2.5 2.3-2.8 Age, years <0.01 <50 1.0 (referent) 50-59 1.2 1.1-1.3 60-69 1.6 1.4-1.7 70-79 2.5 2.3-2.7 >80 7.2 6.4-8.0 Charlson score <0.01 0 1.0 (referent) 1 0.7 0.7-0.7 >1 1.1 1.0-1.3 Clinical T stage <0.01 T1 1.0 (referent) T2 0.7 0.7-0.8 PSA <0.01 <4 1.0 (referent) >4 0.9 0.9-0.9 Hospital type <0.01 Academic 1.0 (referent) Community 0.8 0.8-0.9 Comprehensive 0.5 0.5-0.5 Other 0.5 0.4-0.6 Hospital location <0.01 Midwest 1.0 (referent) Northwest 1.1 1.1-1.2 South 1.1 1.0-1.1 West 1.3 1.3-1.4 * p values <0.01 considered significant. PSA: prostate-specific antigen; OR: odds ratio; CI: confidence interval.
Please note: Illustration(s) are not available due to copyright restrictions.
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|Title Annotation:||ORIGINAL RESEARCH|
|Author:||Maurice, Matthew J.; Zhu, Hui; Abouassaly, Robert|
|Publication:||Canadian Urological Association Journal (CUAJ)|
|Date:||Apr 1, 2015|
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