Search tips
Search criteria 


Logo of jncimonoLink to Publisher's site
J Natl Cancer Inst Monogr. 2012 September; 2012(45): 213–220.
Published online 2012 September 14. doi:  10.1093/jncimonographs/lgs033
PMCID: PMC3540885

Regional, Provider, and Economic Factors Associated With the Choice of Active Surveillance in the Treatment of Men With Localized Prostate Cancer


Data on initial treatment of 8232 cases of localized prostate cancer diagnosed in 2004 were obtained by medical record abstraction (including hospital and outpatient locations) from seven state cancer registries participating in the Centers for Disease Control and Prevention’s Breast and Prostate Cancer Data Quality and Patterns of Care Study. Distinction was made between men receiving no therapy with no monitoring plan (no therapy/no plan [NT/NP]) and those receiving active surveillance (AS). Overall, 8.6% received NT/NP and 4.7% received AS. Older age at diagnosis, lower clinical risk group, and certain registry locations were significant predictors of use of both AS and NT/NP. AS was also related to having more severe comorbidities, whereas nonwhite race was predicted receiving NT/NP. Men receiving AS lived in areas with a higher number of urologists per 100 000 men than those receiving NT/NP. In summary, physician and clinical factors were stronger predictors of AS, whereas demographic and regional factors were related to receiving NT/NP. Physicians appear reluctant to recommend AS for younger patients with no comorbidities.

With recent evidence indicating a lack of large beneficial effect of prostate-specific antigen (PSA) screening in reducing prostate cancer mortality (1), findings that up to 29% of screen-detected prostate cancer is considered to have a low risk of progression after surgical pathology review (2), and concern about potential harm that unnecessary treatment of these cancers may cause (3), the decision to manage patients with low-risk prostate cancer with active surveillance (AS) may be a rational one (4,5). The difficulty lies in identifying the appropriate cohort of prostate cancer patients to manage by this method based on pathological characteristics (6) as well as potential effects on the patient’s long-term quality of life (7).

The physician has been shown to play a major role in the choice of AS (8); however, AS appears to be underused among eligible patients (with only 9% of eligible low-risk patients diagnosed between 1999 and 2004 opting for AS in the Cancer of the Prostate Strategic Urologic Research Endeavor [CaPSURE] study), indicating that the option to pursue AS may not always be offered (9). Previously, the decision to receive no initial therapy (referred to as “expectant management” or “watchful waiting”) was more often considered for elderly men without curative intent. Earlier studies of men diagnosed between 1994 and 2002 indicated that men who were followed by “expectant management” were being seen by primary care physicians as opposed to specialists (10). In contrast, AS is now indicated for younger men with low-risk disease, involves very rigorous follow-up, and includes the option for curative intent, depending on the changes in tumor characteristics during follow-up (11). Thus, physicians’ viewpoint about and their recommendation of this option to their patients are evolving.

We analyzed data on initial treatment of men with localized prostate cancer diagnosed in 2004 from a large population-based sample of cases selected from seven population-based cancer registries in the United States to assess the regional variations, socio-economic factors, and physician characteristics that may be associated with the use of AS, in addition to the demographic and clinical predictors. We compared factors associated with receiving AS to those related to receiving no therapy for the first 6 months after diagnosis with no specific monitoring plan (no therapy/no plan [NT/NP]).


The source of data for these analyses was the Breast and Prostate Cancer Data Quality and Patterns of Care (POC-BP) study, which was funded by the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC), and involved researchers from CDC and seven states (California, Georgia, Kentucky, Louisiana, North Carolina, Minnesota, and Wisconsin). Conducted from 2007 through 2009, the POC-BP study sampled patients diagnosed in 2004 and involved reabstraction of medical records from hospitals and outpatient facilities (ie, pathology laboratories, radiation facilities, free-standing surgery centers, long-term care facilities, and physicians’ offices). Information was collected on the demographic characteristics of the cancer patient, clinical characteristics of their tumor, work-up information, and on the first course of cancer-directed treatment (ie, therapy regimen that was given or planned at the time of the initial cancer diagnosis, prior to disease recurrence or progression). The study was approved by institutional review boards at participating institutions and from six of the seven participating states and at CDC; the seventh state’s institutional review board exempted the study.

From all participating registries, 11 679 cases of invasive prostate cancer (International Classification of Diseases for Oncology, 3rd ed, code C61.9) were randomly selected across strata defined by race/ethnicity and state-specific factors, such as Appalachian vs non-Appalachian region, type of facility, or patient volume of the facility. The methods and quality of the data have been previously described (12). Abstracts were completed for 77.2% (9017) of the selected cases, and 8232 of them had confirmed clinically localized disease (after excluding 363 without sufficient data for risk group classification; 392 with T3 or T4 disease, positive nodes, or metastases; and 30 who had no therapy but died within 6 months of diagnosis).

Demographic Characteristics

Information on patients’ age at diagnosis, race/ethnicity, marital status, and insurance coverage was based on data abstracted from medical records as part of the POC-BP study or, if missing at the time of reabstraction, from the original information abstracted by each participating registry at the time the case was ascertained. The variables were categorized as shown in Table 1.

Table 1.
Weighted percentage of demographic characteristics for men with no therapy by type for men with localized prostate cancer in CDC’s 2004 POC-BP study*

Clinical Characteristics

Clinical information was also based on abstracted information and included clinical T stage, PSA at diagnosis, biopsy-derived Gleason score categorized as shown in Table 2, and clinical recurrence risk group defined according to the National Comprehensive Cancer Network (NCCN) guidelines for Prostate Cancer (version 1.2002) that were in effect at the time these patients were originally diagnosed (13). Specifically, low risk was defined as T1–T2a and Gleason score 2–6 and PSA <10ng/ml. Of the 3242 patients with a T1–T2a stage, 275 had one of the other low-risk variables (ie, either a Gleason Score of 2–6 or a PSA of <10ng/ml) but had missing data on the other variable; these cases were coded as “Low Risk–Missing Data.” Intermediate risk was defined as T2b–T2c or Gleason 7 or PSA 10–20ng/ml. Because patients with T3 disease or higher were not included in this analysis, the high-risk group included patients with Gleason score of 8–10 or PSA >20ng/ml.

Table 2.
Weighted percentage of clinical characteristics for men with no therapy by type for men with localized prostate cancer in CDC’s 2004 POC-BP study*

Comorbidity Definition

The POC-BP Steering Committee selected the Adult Comorbidity Evaluation-27 (ACE-27) to measure comorbidity burden because of its clinical relevance and sensitivity. Developed by Piccirillo et al. (14,15), it is specific for cancer and a significant dose–response relationship between the ACE-27 index and survival has been shown (16,17). The index is based on 26 comorbid conditions, with 3 grades of decompensation (or severity) (17) that were present at or before the date of diagnosis, and excludes complications of cancer or its treatment. The overall comorbidity severity score for the ACE-27 (severe, moderate, mild, or none) used in this analysis was determined by the highest ranking single condition, except when 2 or more grade 2 conditions occurred in different organ systems, in which case the overall comorbidity score was classified as severe (grade 3) (15).

Definition of AS and NT/NP

Patients receiving no therapy within the first 6 months after diagnosis were classified as receiving AS if any evidence of monitoring or specific surveillance or monitoring plan was mentioned in the medical records reviewed. Patients were classified as NT/NP if the patient did not receive therapy within the first 6 months (and was alive 6 months after diagnosis) and no mention or evidence of AS, watchful waiting, expectant management, or other surveillance or monitoring plan was found in the medical records reviewed.

Regional Characteristics

The seven participating registries were from different regions of the United States (including the western, midwestern, eastern, and southern areas). Due to confidentiality restrictions, the specific registries were not identified in the results; however, the variation in use of AS and NT/NP among them was assessed. Other area measures were constructed from 2000 US census data linked to the census tract of the patient’s residence at the time of diagnosis. These ecological measures included percent of the population that was in an urban area (100% urban, 100% rural, urban/rural mix), percent in the working class (< 66% vs ≥66%), percent below the federal poverty level (<20% vs ≥20%), and percent of adults (>25 years old) without a high school education (<25% vs ≥25%). A socio-economic status (SES) index, which had been used in a previous CDC-funded Patterns of Care study, was created based on the poverty level and educational attainment variables (18). The index included three levels: high (defined as being in a census tract with the poverty level <20% and percent without a high school degree <25%), middle (with only one of the indicators in these ranges), and low (with neither of the indicators in these categories).

Physician Characteristics

Information on ratio of urologists per 100 000 men in the county of residence of the patient and on the year of graduation of the urologist providing care was available for cases from six out of the seven participating registries. The numerator data for the number of urologists was obtained from 2004 data from the Area Resource File (19). County-level population estimates for males in 2004 were obtained from Surveillance, Epidemiology, and End Results (SEER) (20). Urologist ratio cutpoints, based on quartiles of the residential distribution of patients, were <2.7, 2.8–5.8, 5.9–9.3, and ≥9.4 (per 100 000 men). The percentage distributions of patients residing in areas of these urologist ratio categories were compared for those receiving AS, NT/NP, and surgery.

The year of medical school graduation for urologists providing AS, NT/NP, and surgery was obtained from the Medicare Physician Identification and Eligibility Registry (MPIER) File, maintained by the US Centers for Medicare and Medicaid Services (21). The years of graduation from medical school were categorized as: before 1970, 1970 through 1979, 1980 through 1989, and after 1990. This information was available for 67% of patients receiving AS, 34% of those with NT/NP, and 72% of those receiving surgery.

Statistical Analysis

The data were weighted using SAS ProcSurveyFreq by the sampling fractions used by each registry for each sampling stratum to represent the source population. Variables were grouped by demographic, clinical, regional, and physician characteristics. The weighted proportion receiving AS and NT/NP was calculated within each category of each variable. The significance of the differences in these proportions between AS and NT/NP was determined by the χ2 statistic.

Separate weighted multivariable models using SAS Proc SurveyLogistic were run to determine factors that independently predicted AS and NT/NP. The urologist ratio and year of urologist graduation were not included in the multivariate models because of their limited availability. The 275 cases in the low-risk group with missing PSA or Gleason score data were excluded from the models because a disproportionate number of them (112 or 43.7%) had NT/NP, and there was concern that these cases may have had missing therapy information as well. For the same concern, those with missing data for marital status, comorbidity burden, and/or insurance coverage (N = 939) were also excluded; thus, the final models included 7018 localized cases with complete data (which represented 85% of localized cases). A second set of models, restricted to those with complete data in the clinical low-risk group (N = 2637), was also run because recommendations for AS may be most appropriate for this subgroup.

Two variables (SES index and clinical risk group) were based on combinations of other variables and thus the components of these measures (ie, poverty level, educational attainment, PSA, Gleason score, and clinical T stage) were not included in the models. Urbanization and proportion in the working class were not included in the final model because they were found to have no association with AS or NT/NP in preliminary models. Categories within some variables were combined due to small numbers. Included as predictor variables in the final models were the demographic variables of age at diagnosis (categorized as <65, 65–74, and ≥75), race/ethnicity (white, all others combined), marital status (married; all others including single, divorced, separated, and widowed combined), insurance status (private including health maintenance organization [HMO]; Medicare with private or HMO supplement; Medicare alone or with military or other governmental coverage; and None and Medicaid combined), SES index (high, middle, low), registry (labeled as A through G), comorbidity burden (none, mild, moderate, severe), and clinical risk group for the localized disease model (low, intermediate, high).


Among patients with localized disease, 13.3% (N = 1138) did not receive therapy in the first 6 months after diagnosis (Table 1), with 4.7% (N = 386) followed by AS and 8.6% (N = 752) by NT/NP. Both of these options were more likely to occur among those aged 75 years and above than among those diagnosed at younger ages; however, there was a gradual increase with age for NT/NP compared with a steep increase in those aged 75 years and above with AS. Nonwhites were more likely than whites to have NT/NP, but racial/ethnic differences were not apparent for use of AS. Men with Medicaid coverage were the most likely to have NT/NP (13.6%), whereas those with Medicare alone or with military or other government insurance were the most likely to receive AS (6.9%).

Men who had a comorbidity burden categorized as severe were more likely to be followed with AS or NT/NP compared with those with lower comorbidity burden, and there was no significant difference in these trends between these two treatment options (Table 2). Although the highest proportions receiving AS and NT/NP were in the lowest risk categories of PSA, Gleason score, and clinical risk group, the proportion receiving AS declined with increasing risk in a consistent manner, whereas there was nonlinear risk for NT/NP. This is shown in the results for the clinical risk group where the proportion receiving AS declined from 6.4% in the lowest risk group to 2.7% in the highest risk group, whereas the proportion with NT/NP was 8.6% in the low-risk group, declined to 6.1% in the intermediate-risk group, and rose to 8.3% in the high-risk group.

The proportion receiving AS varied from 2.8% to 6.9% among the seven registries, whereas the proportion with NT/NP varied from 5.9% to 12.3% (Table 3). Significant differences were found between AS and NT/NP for the poverty level, educational attainment, and SES index variables. The proportion receiving AS was relatively constant among all the categories of these variables, whereas the proportion receiving NT/NP was greater in the lower SES categories of all three measures than in the higher status categories.

Table 3.
Weighted percentage of regional and area characteristics for men with no therapy by type for men with localized prostate cancer in CDC’s 2004 POC-BP study*

Based on the data available for a subset of cases (313 of 386, or 81.1% of those with AS; 695 of 792, or 92.4% of those with NT/NP), the distribution of the patients by categories of the number of urologists per 100 000 men was significantly different between AS patients and those with NT/NP (Figure 1). Over 25% of those receiving AS lived in areas with 9.4 or more urologists per 100 000 men compared with 16% of those who received NT/NP. There was no significant difference in the distribution of AS and NT/NP patients according to year of graduation of their urologist (Table 4); however, those receiving surgery were more likely to be treated by an urologist who was a more recent graduate.

Figure 1.
Percent distribution of localized prostate cancer cases by number of urologists per 100 000 men within county of residence by type of therapy for Centers for Disease Control and Prevention’s 2004 Breast and Prostate Cancer Data Quality and Patterns ...
Table 4.
Weighted percent distribution by year of graduation of urologist for men with localized prostate cancer receiving no therapy vs surgery in CDC’s 2004 POC-BP study*

Multivariable Models

Among all localized cases, older age and severe comorbidity burden significantly increased the risk of receiving AS, whereas men in certain registry locations and in the higher clinical risk groups were less likely to receive it (Table 5). Specifically, those who were 75 years or older at the time of diagnosis were 8.7 (95% confidence level [CL] 5.3 to 14.3) times as likely as those who were under 65 years of age to receive AS, and having a severe comorbidity burden was associated with a risk that was 2.8 (95% CL 1.4 to 5.7) times as high as having no comorbidities. Those in the high clinical risk group were just 0.2 (95% CL 0.1 to 0.3) times as likely to receive AS compared with those in the low-risk group.

Table 5.
Adjusted odd ratios and 95% CL for receiving no therapy by type for all localized prostate cancer patients and those in low clinical risk group in CDC’s 2004 POC-BP study*

NT/NP was also more likely to occur in older men; however, the relationship with age was not as strong as for AS. Those older than 75 years were 2.1 (95% CL 1.5 to 3.0) times as likely to have NT/NP compared with men under 65 years of age. There was no association with comorbidity burden and, although there was an inverse association between use of NT/NP and clinical risk group, it was not as strong as for AS. In addition to significant variation by registry location, NT/NP was also more likely to occur among nonwhites who were 1.7 (95% CL 1.3 to 2.3) times as likely to receive this option compared with whites.

There was no significant association between use of AS or NT/NP and marital status, insurance coverage, or SES index.


Using a large population-based sample of localized prostate cancer cases from diverse regions of the country diagnosed in 2004, we found that AS was used to manage 4.7% of all men sampled and by 6.4% of those in the clinically low-risk disease category. With older age and severity of comorbidities being the strongest predictive factors for its use, it is clear that the practice of recommending AS for the healthy younger man with low-risk disease was not widely adopted at that time. The association of use of AS with older age was similar to that reported in the CaPSURE study based on men diagnosed between 1999 and 2004, where older age was the only demographic predictor (9). Although they found a somewhat higher proportion of the lower risk men using AS (9%), they were able to more specifically identify very low-risk men based on PSA density and number of positive biopsy cores, which were not available in this study.

These findings suggest that physicians still feel more comfortable recommending AS for men with lower life expectancy and more severe comorbidities that may preclude use of surgery or other aggressive therapy. Thus, physicians may be unwilling to recommend AS for younger men or those without comorbidities due to uncertainty regarding which selection criteria to use and due to patients’ anxiety about monitoring their disease instead of having definitive treatment. In one study examining urologists recommendations for low-risk prostate cancer, AS was discussed 25% of the time vs 80% for prostatectomy (22).

In addition to those receiving AS, we found that 8.6% received NT/NP, bringing the total proportion of men receiving no therapy in the first 6 months after diagnosis to 13.3%. In another registry-based patterns of care study by the National Cancer Institute’s SEER cancer registries, no treatment (due to any reason) within the first 6 months after diagnosis was found for 12.6% of men with clinically localized prostate cancer in 1998 and 9% in 2002 (23). It is possible that there was some increase in the overall proportion receiving no therapy between 2002 and 2004, but it cannot be determined if it was due to an increase in those receiving AS vs having NT/NP or due to differences in the characteristics of the patients included in each of these studies.

In contrast to those receiving AS, we found that men with NT/NP were more likely to be from areas with fewer urologists and also more likely to be nonwhite. In the univariate analyses, they were also more likely to be from lower socio-economic areas, although this variable was not significant in the multivariable models. Because no specific mention of any form of observation was indicated in the medical record, these men may have taken longer to decide on what therapy to pursue or may be having delays in receiving care due to problems with access to care. From additional review of the medical record data in the POC-BP study, we found that 35% of them (compared with less than 5% of AS patients) did receive some type of therapy after 6 months, indicating that delay in therapy was an important factor for men in the NT/NP group. The men with delay were more likely to be younger than those who continued with no therapy and were also more likely to be in the lowest clinical risk group.

Another concern with the NT/NP group is that medical records containing information about their therapy may have been missing or unavailable for abstraction. Although we removed patients with missing data in other variables from the multivariable models, we had an additional variable on the source of information abstracted for each case and found that (after removing those with missing data) physician office records were less likely to be reviewed for the NT/NP group compared with those receiving AS (44.2% vs 69.4%), thus missing outpatient treatment information may also be a factor.

Although registry-based studies are helpful in deriving population-based estimates of use of specific therapies, there are limitations in the types of data that are available. Only data available for abstraction in medical records are included, and although efforts were made to obtain physician and outpatient records, this was not possible for all cases. Thus, information about use of specific monitoring plans may be underreported. Other sources of data including claims information, or additional review of medical records for evidence of repeat PSAs, or return visits to urologists or radiation oncologists during the 6-month period after diagnosis may provide evidence of monitoring, even if not explicitly stated in the medical record. This type of information was not available for this study, however. Another limitation is the year of diagnosis (2004) on which these results are based. Although we were able to compare use of AS with other data sources from this same time period, the currently changing viewpoint on use of AS, especially regarding its use for younger men with potentially curable disease, is a more recent development, which may not have been widely accepted at the time these men were diagnosed. Nevertheless, the data presented here provide an important baseline for assessing changes in the use of this management option. In order to be able to do this using cancer registry data, which routinely include PSA, biopsy-derived Gleason score, and clinical T stage, there are other AS selection criteria proposed, such as PSA density, tumor percentage within biopsy cores, as well as number of positive biopsy cores (24) that should be abstracted in future studies. If definitive AS selection criteria could be determined from the different options being considered (6), cancer registries could be a valuable resource to obtain additional predictors of progression that could be used to assess the number of patients that may ultimately benefit from AS and monitor the use of this approach among clinically eligible men from a population-based perspective.


This work was supported by the Centers for Disease Control and Prevention through cooperative agreements with the California Cancer Registry (Public Health Institute) (1-U01-DP000260); Emory University (1-U01-DP000258); Louisiana State University Health Sciences Center (1-U01-DP000253); Minnesota Cancer Surveillance System (Minnesota Department of Health) (1-U01-DP000259); Medical College of Wisconsin (1-U01-DP000261); University of Kentucky (1-U01-DP000251); and Wake Forest University (1-U01-DP000264).



The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.


1. Chou R, Croswell JM, Dana T, et al. Screening for prostate cancer: a review of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2011; 155(11):762–771 [PubMed]
2. Epstein JI, Walsh PC, Carmichael M, Brendler CB. Pathologic and clinical findings to predict tumor extent of non-palpable (stage T1c) prostate cancer. JAMA. 1994; 271(5):368–374 [PubMed]
3. Brawley OW. The prostate cancer quandary. American Cancer Society Web site. Published June 29, 2011. Updated October 5, 2011. Accessed July 10 2012;
4. Klotz L. Active surveillance for prostate cancer: a review. Curr Urol Rep. 2010; 11(3):165–171 [PubMed]
5. Albertsen PC. Treatment of localized prostate cancer: when is active surveillance appropriate?. Nat Rev Clin Oncol. 2010; 7(7):394–400 [PubMed]
6. Suardi N, Capitanio U, Chun FK, et al. Currently used criteria for active surveillance in men with low-risk prostate cancer: an analysis of pathologic features. Cancer. 2008; 113(8):2068–2072 [PubMed]
7. Hayes JH, Ollendorf DA, Pearson SD, et al. Active surveillance compared with initial treatment for men with low-risk prostate cancer: a decision analysis. JAMA. 2010; 304(21):2373–2380 [PMC free article] [PubMed]
8. Gorin MA, Soloway CT, Eldefrawy A, Soloway MS. Factors that influence patient enrollment in active surveillance for low-risk prostate cancer. Urology. 2011; 77(3):588–591 [PubMed]
9. Barocas DA, Cowan JE, Smith JA, Jr, Carroll PR. CaPSURE Investigators. 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(4):1330–1335 [PubMed]
10. Jang TL, Bekelman JE, Liu Y, et al. Physician visits prior to treatment for clinically localized prostate cancer. Arch Intern Med. 2010; 170(5):440–450 [PubMed]
11. Brewster SF. Low-risk localized prostate cancer: are we ready to tell patients that active surveillance is the preferred option?. BJU Int. 2008; 102(8):923–926 [PubMed]
12. German RR, Wike JM, Bauer KR, et al. Quality of cancer registry data: findings from CDC-NPCR’s Breast and Prostate Cancer Data Quality and Patterns of Care Study. J Registry Manag. 2011; 38(2):75–86 [PubMed]
13. National Comprehensive Cancer Network (NCCN) NCCN Clinical Practice Guidelines in Oncology, Prostate Cancer 2002. Accessed August 1, 2012.
14. Piccirillo JF, Creech C, Zequeira R, Anderson S, Johnson AS. Inclusion of comorbidity into oncology data registries. J Registry Manag. 1999; 26(2):66–70
15. Johnson AS, Piccirillo JF, Creech C, et al. Validation of a comorbidity education program. J Registry Manag. 2001; 28(3):125–131
16. Piccirillo JF, Costas I, Claybour P, Borah AJ, Grove L, Jeffe D. The measurement of comorbidity by cancer registries. J Registry Manag. 2003; 30(1):8–14
17. Piccirillo JF, Tierney RM, Costas I, Grove L, Spitznagel EL., Jr Prognostic importance of comorbidity in a hospital-based cancer registry. JAMA. 2006; 291(20):2441–2447 [PubMed]
18. Byers TE, Wolf HJ, Bauer KR, et al. The impact of socioeconomic status on survival after cancer in the United States: findings from the National Program of Cancer Registries Patters of Care Study. Cancer. 2008; 113(3):585–591 [PubMed]
19. Area Resource File (ARF) National County-level Health Resource Information Database. Rockville, MD: Health Resources and Services Administration; 2009; Accessed July 10 2012.
20. US Population Data – 1969-2009. SEER Surveillance Epidemiology, and End Results Web site. Published January 21, 2011. Accessed July 10 2012.
21. Caldwell D. Medicare physician identifiers UPINs, PINs and NPI numbers. Research Data Assistance Center Publication Number TB-002. Published January2003. Accessed July 102012.
22. Ramsey SD, Zeliadt SB, Fedorenko CR, et al. Patient preferences and urologists recommendations among local stage prostate patients who present for initial consultations and second opinions. World J Urol. 2011; 29(1):3–9 [PubMed]
23. Hamilton AS, Albertsen PC, Johnson TK, et al. Trends in treatment of localized prostate cancer using supplemented cancer registry data. BJU Int. 2011; 107(4):576–584 [PubMed]
24. Dall’Era MA, Konety BR. Active surveillance for low-risk prostate cancer: selection of patients and predictors of progression. Nat Rev Clin Oncol. 2008; 5(5):277–283 [PubMed]

Articles from Journal of the National Cancer Institute. Monographs are provided here courtesy of Oxford University Press