- Email: [email protected]
Making Sense of Prostate Specific Antigen: Improving its Predictive Value in Patients Undergoing Prostate Biopsy
Making Sense of Prostate Specific Antigen: Improving its Predictive Value in Patients Undergoing Prostate Biopsy Robert K. Nam,* Ants Toi, John Trachtenberg, Laurence H. Klotz, Michael A. S. Jewett, Marjan Emami, Linda Sugar, Joan Sweet, Greg R. Pond and Steven A. Narod From the Division of Urology (RKN, LHK, ME, GRP) and Department of Pathology (LS), Sunnybrook and Women’s College Health Sciences Centre, Division of Urology (JT, MASJ), Department of Medical Imaging (AT) and Department of Pathology (JS), University Health Network and Department of Public Health Sciences (SAN), University of Toronto, Toronto, Ontario, Canada
Purpose: The clinical usefulness of PSA for prostate cancer screening is unclear, although the test remains in common use. New methods to interpret PSA are needed. Materials and Methods: We examined a cohort of 2,637 men who underwent prostate biopsies for abnormal DRE or PSA between 1999 and 2004. Using risk factors for prostate cancer, including patient age, ethnicity, family history of prostate cancer, previous negative biopsy, voiding symptoms and prostate volume, we developed risk groups for prostate cancer using recursive partitioning modeling independent of PSA or DRE. We then compared prostate cancer probabilities by PSA ranges by risk group. Results: Of the 2,637 men 1,282 (48.6%) had prostate cancer. Age, ethnicity, family history, previous negative biopsy and prostate volume were predictive for cancer. We constructed 6 risk groups by combining these factors and created tables to assign patients to these groups. Independent of PSA and DRE the probability of cancer ranged from 15% in patients in group 1 to 78% in patients in group 6 (p ⬍0.0001). By adding PSA and DRE to each risk group prostate cancer probabilities were refined from 0% to 100%. Patients in the higher risk groups also had higher grade cancer (p ⬍0.0001). Conclusions: We generated 6 risk groups based on simple risk factors for prostate cancer. When used in the right context and patient, PSA is highly accurate for predicting prostate cancer and permitting rational decision making in patients with abnormal PSA. Key Words: prostate, prostatic neoplasms, prostate-specific antigen, risk
Several strong risk factors for prostate cancer have been identified, including patient age, ethnic group and a family history of prostate cancer.3,4 Other factors, such as prostate volume and DRE, are also important for determining the risk of prostate cancer.5,6 To our knowledge no study to date has examined in detail how the combination of these risk factors affects the risk of prostate cancer at a given PSA. By establishing different risk profiles in patients based on these factors the risk of prostate cancer could be estimated prior to biopsy and then modified, given a specific PSA. These estimates could aid clinicians and patients in decision making in men faced with abnormal PSA. We examined a cohort of 2,637 patients who underwent 1 or more prostate biopsies in the context of a PSA screening program. We first examined factors that were positively associated with prostate cancer independent of PSA and DRE. Using recursive partitioning modeling we created low to high risk groups for prostate cancer based on a combination of these risk factors for prostate cancer. Finally, estimates of the probability of prostate cancer were modified based on PSA and DRE groupings for each risk group. Using these groupings we were able to dramatically improve our ability to estimate the risk of prostate cancer in an individual for a given PSA and DRE status. Tables were constructed to be able to assign a given patient to these risk groups based on these factors.
t has been questioned whether PSA is an effective screening instrument for prostate cancer management.1,2 Stamey et al argued that the “prostate specific antigen era . . . is over for prostate cancer.”2 This statement was based on studies showing that serum PSA no longer accurately distinguishes patients with prostate cancer from those with benign prostatic hyperplasia at PSA less than 20 ng/ml.2 Another group noted that the prevalence of prostate cancer in men was unexpectedly high (24.4%) in the placebo arm in a randomized study of prostate cancer prevention.1 Thus, there is uncertainty in using PSA as a screening instrument for prostate cancer among decision makers, physicians and patients. Previously established prostate cancer rates in patients with abnormal PSA may not be valid, leading to confusion as to how to interpret PSA. Despite this confusion PSA testing continues to be widely used for prostate cancer screening. Guidelines are needed to interpret the significance of PSA for prostate cancer.
I
Submitted for publication March 22, 2005. Study received hospital research ethics board approval. Supported by National Cancer Institute of Canada Grant 010284, National Cancer Institute of Canada Terry Fox Foundation Grant 015168 and the Canadian Urological Association Scholarship Fund (RKN). * Correspondence: 2075 Bayview Ave., MG-406, Toronto, Ontario, Canada, M4N 3M5 (telephone: 416-480-5075; FAX: 416-480-6121; e-mail: [email protected]).
0022-5347/06/1752-0489/0 THE JOURNAL OF UROLOGY® Copyright © 2006 by AMERICAN UROLOGICAL ASSOCIATION
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Vol. 175, 489-494, February 2006 Printed in U.S.A. DOI:10.1016/S0022-5347(05)00159-X
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METHODS Study subjects. Patients were drawn from a sample of 2,838 eligible men who were referred to the prostate centers at our institution (Sunnybrook and Women’s College Health Sciences Centre, and University Health Network) between June 1999 and June 2004. Patients were included in the study if PSA was greater than 2.5 ng/ml7 or they had abnormal DRE. All patients underwent TRUS and 1 or more prostate biopsies. In Ontario, Canada there are no formal criteria for PSA screening but the practice is widespread. It is important to note that in Canada everyone is insured by a public health insurance system. However, patients eligible for this study were unselected and accrued consecutively. No patient had a history of prostate cancer prior to prostate biopsy. Of the 2,839 men 46 were not capable of providing consent to participate in a research study. Of the remaining 2,793 men 2,637 (94%) consented to participate. All research was performed with informed consent and with the approval of the hospital research ethics board. Baseline data information and primary end point. A urological voiding history (American Urological Association symptom score8), DRE results, serum PSA, family history of prostate cancer information and ethnic background were determined by research personnel through questionnaire administration and all data were stored in a centralized database. Prostate volume was measured by TRUS. Volume was determined by 2 physicians with extensive experience performing TRUS and prostate biopsy (RKN and AT). It was estimated using the formula found to have the best accuracy for prostate volume, that is length in mm ⫻ width in mm ⫻ sagittal height in mm ⫻ 0.0005236 ⫽ volume in cc,9 where length and height are measured on the mid sagittal view and width is measured on the on transverse axial view. Six to 15 ultrasound guided needle core biopsies (median 8) were performed using an 18 gauge spring loaded biopsy device. Samples were obtained using a systematic pattern and additional targeted samples were obtained from suspicious areas. The primary end point was the histological presence of adenocarcinoma of the prostate in the biopsy specimen. All grading was based on the Gleason scoring system. All histological interpretations were interpreted by 2 experienced genitourinary pathologists (LS and JS). We6 and others10 have reported that approximately 15% to 30% of patients have cancer on repeat prostate biopsy after an initial negative biopsy. Therefore, patients who had an initial negative biopsy were offered repeat prostate biopsies. Of the 2,637 patients 1,166 (44.2%) had cancer. Of the remaining 1,471 men who did not have cancer 408 underwent 1 or more repeat prostate biopsies, of whom 116 (28.4%) had cancer. We did not consider men who underwent more than 1 repeat biopsy after previous negative biopsies as a separate variable due to small sample size (69) and they were grouped with the 408 patients. Of the 2,637 patients 1,282 (48.6%) had cancer (cases) and 1,355 (51.4%) had no evidence of cancer (controls). Data analysis. Cases were defined as patients with adenocarcinoma of the prostate on any biopsy and controls were defined as having no evidence of cancer on any biopsy. Potential factors associated with increased prostate cancer risk were compared between cases and controls, including age,
ethnicity, family history of prostate cancer, prostate volume, LUTS, PSA and DRE. We did not consider the number of needle cores obtained as a potential predictor because we have previously observed that it is not a predictor for prostate cancer.6 Unconditional logistic regression analysis was used to estimate the OR for prostate cancer detection for each of these factors alone and in combination. To improve the positive predictive value for prostate cancer detection by PSA and DRE results we created risk groups by factors that we have found are associated with prostate cancer, including age, ethnicity, family history of prostate cancer, prostate volume and LUTS, as described.3,4 We also considered whether a patient had a previous negative biopsy. Using these risk groups we estimated the risk of prostate cancer according to PSA and DRE result. We created specific tables to show how the combination of factors affects the risk of prostate cancer in a given patient. Creation of risk groups. To derive risk groups for prostate cancer we divided the 2,637 patients into 2 separate data sets (at random) to create an analysis data set comprising of 2,100 (80%) and a validation data set of 537 (20%). Patients included in the analysis data set were used to construct risk groups based on the demographic and clinical predictors. The accuracy of the risk groups proposed using the analysis data set were then evaluated using the validation data set. To determine whether correct assignments to risk groups were made the probability of prostate cancer by each risk group was compared between the analysis and validation data sets. We used recursive partitioning analysis to create a classification tree for modeling predictor variables.11 Predictor variables were age at biopsy, ethnicity, family history of prostate cancer, previous negative biopsy, prostate volume and LUTS. The data were successively split according to each possible binary grouping of patients and nodes were defined by which the split created 2 groups of patients with the maximally distinguishable difference in the outcome variable, ie cancer. Splitting was stopped when any branch contained fewer than 30 patients. Statistical significance was defined as p ⬍0.05. Branches were tested for differences using the 2-sided chi-square test, adjusting for multiple comparisons (significance at Bonferroni corrected p ⫽ 0.0028). The additional information provided by DRE and PSA testing was evaluated in each proposed risk group using the Cochran-Armitage test for trend. Correlations with histological grade were also investigated. We categorized age at biopsy by decades and prostate volume by its quartile distribution. RESULTS Mean age at biopsy in the 2,637 men was 64.8 years (range 39.9 to 93.8). Mean PSA was 10.8 ng/ml (median 7.28, range 0.05 to 498.8), while 38.4% of the men had abnormal DRE. The majority of the patients were white (2,181 or 82.7%), while 253 (9.6%) and 133 (5.0%) were black and Asian, respectively. Of the patients 13% had at least 1 relative with prostate cancer. Of the 2,637 men 1,282 (48.6%) were found to have adenocarcinoma of the prostate at biopsy (cases) in 1 or more biopsies and 1,355 (51.4%) had no evidence of cancer (controls). Of the 1,282 men with cancer 24 (1.9%), 531 (41.4%),
MAKING SENSE OF PROSTATE SPECIFIC ANTIGEN
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TABLE 1. Prostate cancer factors in cases and controls, and multivariate analysis of factors related to prostate cancer Factor No. Subjects (%)
Ca 1,282 (48.6)
No Ca 1,355 (51.4)
p Value
Adjusted OR* (95% CI)
p Value
Mean age ⫾ SD No. family history (%): Absent Present No. ethnicity (%): Asian White Black Other LUTS: Absent Present Median cc prostate vol (range) No. DRE (%): No nodule Nodule Median ng/ml PSA (range) No. previous neg biopsy (%): No Yes
66.0 ⫾ 8.5
63.6 ⫾ 8.1
⬍0.0001
1.05† (1.03–1.05)
⬍0.0001
1,083 (47.5) 199 (56.1)
1,199 (52.5) 156 (43.9)
0.003
39 (29.3) 1,072 (49.2) 144 (56.9) 27 (38.6)
94 (70.6) 1,109 (50.8) 109 (43.1) 43 (61.4)
⬍0.0001
774 (51.3) 508 (45.0) 47.0 (15–295)
734 (48.7) 621 (55.0) 61.0 (15–295)
943 (45.3) 339 (61.0) 7.85 (0.6–498.8) 1,166 (52.3) 116 (28.4)
0.001 ⬍0.0001
1,138 (54.7) 217 (39.0) 6.76 (0.05–132.4)
⬍0.0001
1,063 (47.7) 292 (71.6)
⬍0.0001
⬍0.0001
1.00 1.41 (1.1–1.8)
0.007
1.00‡ 2.49 (1.8–3.5) 3.75 (2.4–5.7)
⬍0.0001 ⬍0.0001
1.00 0.86 (0.7–1.0) 0.98† (0.97–0.99)
0.09 ⬍0.0001
1.00 1.48 (1.2–1.8) 1.07† (1.05–1.08)
0.0003 ⬍0.0001
1.00 0.45 (0.4–0.6)
⬍0.0001
* Multivariate model includes age at biopsy, family history of prostate cancer, ethnicity, LUTS, prostate volume, DRE, PSA and previous negative biopsy. † Age at biopsy per year, prostate volume per cc and PSA/ng/ml considered continuous variables in the multivariate model. ‡ Baseline group defined as Asian and other.
565 (44.1%) and 162 (12.6%) had Gleason score 4 or 5, 6, 7 and 8 to 10, respectively. All risk factors for prostate cancer were found to be significantly associated with prostate cancer (table 1). On multivariate analysis all factors were independently associated with prostate cancer risk (table 1). In particular patients who had an initial negative biopsy were at a lower risk for prostate cancer at repeat biopsy (adjusted OR 0.45, p ⫽ 0.0001). Results of classification tree for risk factors for prostate cancer without PSA or DRE. Of the 2,637 patients 2,100 were placed in the analysis data set and 537 were in the validation data set. There were no significant differences in baseline characteristics between the 2 groups with respect to age, ethnicity, family history of prostate cancer, prostate volume, LUTS, PSA and DRE (data not shown). In the recursive model 6 distinct groups of combinations of risk factors for prostate cancer were created from the classification tree. Age, ethnicity, family history of prostate cancer, prostate volume and previous negative biopsy were important factors for determining the groupings. Only LUTS did not contribute independent information in the recursive model. Multiple combinations of these factors determined and categorized into the 6 distinct risk groups from the recursive model showed significant differences in prostate cancer risk
across the groups (p ⬍0.0001, table 2). Group 1 had the lowest percent prostate cancer risk (14.9%) and group 6 had the highest prostate cancer risk (78.2%). Table 3 shows how the combinations of risk factors were assigned by the model to each of the 6 groups in all patients. Using table 3 a risk group category can be assigned based on the age, ethnicity, family history of prostate cancer, previous negative biopsy and prostate volume in an individual. When applied to patients in the validation data set, the results were similar (table 2). We also examined whether the risk groups were predictive for prostate cancer after adjusting for DRE and PSA in a multivariate model. The adjusted OR for prostate cancer in patients in groups 6 to 2 were 31.8 (95% CI 17.2 to 58.7, p ⬍0.0001), 19.3 (95% CI 10.3 to 36.0, p ⬍0.0001), 11.0 (95% CI 6.1 to 19.6, p ⬍0.0001), 4.74 (95% CI 2.7 to 8.5, p ⬍0.0001) and 3.28 (95% CI 1.8 to 5.8, p ⬍0.0001), respectively, when using group 1 as the baseline group. To determine whether the groupings predicted patients who had aggressive prostate cancer we compared the distribution of histological grade at diagnosis among the risk groups regardless of PSA or DRE. The 6 risk factor groups were significantly associated with grade at diagnosis. Patients in the lowest risk group had a lower proportion of high grade (Gleason score 7 or more) cancers than patients in the highest risk group (0% vs 71.4%, p ⬍0.0001, table 4).
TABLE 2. Probability of cancer by risk group with comparison between analysis and validation data sets Analysis Data Set Group
% Prostate Ca Risk (No. pts)*
1 2 3 4 5 6
14.9 (13) 29.6 (189) 42.8 (171) 56.1 (262) 66.0 (126) 78.2 (247)
Validation Data Set No. Pts
% Prostate Ca Risk (No. pts)
95% CI
No. Pts
87 639 400 467 191 316
8.0 (2) 34.3 (57) 39.6 (38) 60.7 (71) 70.4 (38) 86.1 (68)
(1.0–26.0) (27.2–42.1) (29.7–50.1) (51.2–69.6) (56.4–82.0) (76.5–92.8)
25 166 96 117 54 79
* For 2 ⫻ 6 table comparing cancer vs controls across the 6 risk groups chi-square 371.7, p ⬍0.0001.
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TABLE 3. Patient grouping by risk factors for prostate cancer independent of PSA or DRE, as determined by recursive partitioning model Prostate Vol (cc) Age White, no previous biopsy: Younger than 50 50–60 60–70 Older than 70 Black, no previous biopsy: Younger than 50 50–60 60–70 Older than 70 Asian/other, no previous biopsy: Younger than 50 50–60 60–70 Older than 70 Initial neg biopsy, any ethnic background: Younger than 50 50–60 60–70 70 or Older
Less Than 40
40–55
55–75
75 or Greater
2 4 5 6
2 4 4 (neg FH), 5 (pos FH) 6
2 3,5 3 (neg FH), 5 (pos FH) 4
2 2 2 3
2 6 6 6
2 6 6 6
2 3 (neg FH), 5 (pos FH) 3 (neg FH), 5 (pos FH) 4
2 2 2 3
2 2 2 6
2 2 2 6
2 2 2 4
2 2 2 3
2 2 2 2
2 2 2 2
2 2 2 2
1 1 1 3
Using this table a patient can be assigned to group 1 to 6 according to age, prostate volume, ethnicity, prostate cancer family history and whether previous initial biopsy was negative.
Probability of prostate cancer by PSA and DRE based on risk groups. We calculated the probability of prostate cancer by PSA and DRE status in patients in each of the 6 risk groups (table 5). To increase study power we combined the analysis and validation data sets. For each PSA category the probability of cancer varied widely among risk groups. For PSA 0 to 3.99 ng/ml the probability increased from 0% to 55.6% depending on the risk group, for 4.0 to 9.99 ng/ml the probability increased from 11.1% to 90.9% depending on the risk group, for 10.0 to 19.99 ng/ml the probability increased from 3.3% to 92.6% depending on the risk group and for values greater than 20.0 ng/ml the probability increased from 0% to 100% depending on the risk group. PSA categories were also able to further distinguish grade at diagnosis. DISCUSSION We provide a clinical instrument for physicians to help determine the risk of prostate cancer in a patient with abnormal PSA or DRE. Using table 3 physicians will be able to determine the risk group of the patient and estimate his underlying risk of prostate cancer and the likelihood of an aggressive form of cancer. Using table 5 a specific probability for prostate cancer can be determined based on PSA and DRE status. These estimates will allow more informed decision making by physicians and patients when considering prostate biopsies, particularly when aggressive forms of
prostate cancer can be predicted. However, it is important to note that these results apply to men with abnormal PSA or DRE, in contrast to a general screening population. To illustrate this, in large cohort and screening studies the probability of prostate cancer in patients with PSA 4.0 to 10.0 ng/ml is 30% to 50%.10,12 These intermediate estimates make it difficult to interpret the risk of prostate cancer in a patient. From our study we can now provide a better estimate of the risk of prostate cancer in patients who are in this range. Specifically in patients with normal DRE and PSA 4.0 to 10.0 ng/ml the risk is 15%, 30%, 40%, 57%, 67% and 75% in groups 1 to 6, respectively. In patients with abnormal DRE the risk ranges from 11% in group 1 to 91% in group 6. Furthermore, the risk of high grade cancer in this PSA range is highest in groups 3 to 6. With these refined probabilities for prostate cancer based on PSA and DRE using these risk groups biopsy management strategies can be improved. For example, in patients at 90% or more risk for prostate cancer with an initial negative biopsy repeat biopsy would be clearly indicated, particularly when the odds of having high grade cancer are found to be high based on risk group and PSA. Also, patients with normal PSA (less than 4 ng/ml) but in a high risk group (5 or 6) should undergo biopsy, given a probability of up to 50% for prostate cancer and the increased likelihood of high grade disease based on risk group alone. On the other hand, pa-
TABLE 4. Histological grade by risk group
Group
% Prostate Ca* Risk (No./total No.)
1 2 3 4 5 6
13.4 (15/112) 30.6 (246/805) 42.1 (209/496) 57.0 (333/584) 66.9 (164/245) 79.7 (315/395)
No. Gleason Score
(%)†
Low
High
High/Low
15 (100.0) 167 (68.9) 89 (42.6) 129 (38.7) 65 (39.6) 90 (28.6)
0 79 (32.1) 120 (57.4) 204 (61.3) 99 (60.4) 225 (71.4)
0/1 0.5/1 1.3/1 1.6/1 1.5/1 2.5/1
* Based on combined analysis and validation dataset groups (2,637 patients). † Distribution of Gleason scores 4 to 6 (low) vs 7 to 10 (high) across 6 risk groups 2 ⫻ 6 table chi-square 111.8. (p ⬍ 0.0001).
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TABLE 5. Cancer probability according to risk group by PSA in patients with normal and abnormal DRE % PSA (No./total No.) Group Normal: 1 2 3 4 5 6 Abnormal: 1 2 3 4 5 6
0–3.9 Ng/Ml
4.0–9.9 Ng/Ml
10.0–19.9 Ng/Ml
Greater Than 20.0 Ng/Ml
p Value
50.0 (1/2) 14.3 (7/49) 5.6 (1/18) 23.4 (15/64) 25.8 (8/31) 51.9 (14/27)
15.3 (9/59) 29.8 (128/430) 39.5 (92/233) 57.3 (153/267) 66.7 (76/114) 75.2 (109/145)
3.3 (1/30) 34.1 (61/179) 44.2 (46/104) 60.8 (48/79) 85.3 (29/34) 83.1 (49/59)
14.3 (1/7) 54.1 (20/37) 39.5 (17/43) 73.3 (22/30) 71.4 (5/7) 93.9 (31/33)
0.17 ⬍0.001 0.06 ⬍0.001 ⬍0.001 ⬍0.001
0.0 2.5 (1/40) 16.7 (2/12) 18.4 (7/38) 40.0 (6/15) 55.6 (15/27)
11.1 (1/9) 34.7 (17/49) 53.6 (30/56) 80.8 (59/73) 91.7 (33/36) 90.9 (50/55)
40.0 (2/5) 47.1 (8/17) 57.9 (11/19) 87.0 (20/23) 83.3 (5/6) 92.6 (25/27)
0.0 39.5 (4/4) 90.0 (10/11) 90.0 (9/10) 100.0 (2/2) 100.0 (22/22)
0.51 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001
tients at less than 15% risk for prostate cancer may consider not undergoing biopsy, particularly if they are in a risk group and at a PSA where there is a high chance of low grade disease. Also, the prevalence of prostate cancer may be as high as 15% in patients with normal PSA based on the Prostate Cancer Prevention Study.1 The concept of using risk factors for prostate cancer to interpret the significance of abnormal PSA is not new. However, to our knowledge no group has estimated the precise risk of prostate cancer based on combining these multiple factors in a clinical setting. Narod et al were the first to estimate the risk of prostate cancer based on a family history of prostate cancer in a large screening study but they not consider other risk factors.4 Although age and prostate volume have been considered individually to adjust PSA,5 no clinically accepted standard has been created. A possible reason may be due to the variability in interpreting prostate volume on ultrasonography.13 This would be an important issue to consider in our study since prostate volume was an important predictor. However, the quartile cutoffs are within reported measurement error limits and a higher degree of volume measurement error primarily occurs with large prostates, that is beyond 75 cc,13 which was our fourth quartile. Furthermore, our data clearly show that multiple factors, including ethnic background and family history of prostate cancer, are important when estimating the risk of prostate cancer with PSA and DRE. Another consideration is that prostate volume assessment will be required prior to biopsy to estimate the risk of prostate cancer. Although transrectal ultrasound alone has not been used as a single diagnostic test, it would be required to obtain an accurate prostate volume measurement. However, other, less invasive imaging techniques could be used to estimate prostate volume. Another consideration is the measurement of transition zone volume. Ohigashi et al recently reported that transition zone epithelial volume independently predicted prostate cancer in patients with PSA 4.0 to 10.0 ng/ml.14 A limitation of this study is that transition zone volumes were not measured. Future confirmatory studies should also consider transition zone volume to refine the risk groupings. Stamey et al examined 1,317 patients who underwent surgery and compared PSA with respect to the volume of prostate cancer and benign prostatic hyperplasia tissue.2 They concluded that PSA (less than 20 ng/ml) was only related to the amount of benign prostate tissue present.
However, they did not compare these patients to normal controls and did not consider how other prostate cancer risk factors could have affected their analysis. Also, in the Prostate Cancer Prevention Study Thompson et al reported a 24.4% prevalence of prostate cancer in 4,692 men in the placebo arm.1 However, they also did not stratify by other risk factors for prostate cancer when reporting cancer prevalence rates. We acknowledge that some estimates of prostate cancer risk did not show a significant trend by PSA categories. In some subgroups this may have been due to lack of sample size in each subgroup, particularly in patients in group 1. However, in this group it may be possible that PSA is not predictive of prostate cancer, although Group 1 only consisted of 4% of the study population (102 of 2,637 men). Patients in group 1 were those with a previous negative biopsy, prostate volume 75 cc or greater and age less than 70 years. We6 and others15 have reported that in patients who undergo repeat biopsy after negative initial biopsy PSA is not an important predictor of prostate cancer. It is important to consider whether patients had an initial negative biopsy in the recursive model, given the 15% to 30% prevalence of prostate cancer after repeat biopsy.6,10 Cancer lesions may be missed on initial biopsy due to sampling error. Thus, the prediction model had to consider whether a patient had had a previous negative biopsy, given that it could affect the risk of prostate cancer. Although not all patients underwent repeat biopsy after an initial negative biopsy, the majority of repeat biopsies were done because of persistent abnormal PSA or HGPIN.6 We did not consider HGPIN separately in the model since a primary indication for repeat biopsy was HGPIN. Including a HGPIN variable and a previous negative biopsy variable would have resulted in co-linearity in the regression model (table 1). Thus, only 1 variable was used. We16 and others17 have examined other biomarkers, including free and complexed PSA, and human kallirein-2, but their additional predictive value was not significantly better for all levels of total PSA. Of these biomarkers only the free-to-total PSA ratio provided additional predictive information for PSA 4.0 to 10.0 ng/ml.5 However, to our knowledge no standard cutoffs for the free-to-total PSA ratio have been established. None have been able to significantly distinguish low and high grade cancers, which we were able to do based on risk factors alone. Finally, the role of free-to-
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total PSA is limited to patients with total PSA less than 10 ng/ml. The observation that risk groups were significantly associated with grade at diagnosis was unexpected. To our knowledge this association has not been described previously. Particularly in group 6 patients were at a greater than 2-fold increased risk for high vs low grade cancer (table 4). When we examined any possible correlations with the factors individually with grade, no single factor was found to be significantly associated with grade (data not shown). However, in combination patients in higher risk groups were found to be at higher risk for high grade cancer. It is possible that a family history of prostate cancer may be an important factor in this association. Kupelian et al observed that a family history of prostate cancer may indicate a worse prognosis in patients with localized disease compared to patients without a family history of cancer.18 It is likely that patients have a genetic predisposition toward aggressive or nonaggressive prostate cancer. Polymorphisms of various candidate genes have been associated with advanced prostate cancer.19 Mutations of RNAsel, the putative gene for HPC1 found by linkage, have also been implicated in an association with advanced prostate cancer.20 Subsequent prediction models should be extended to include new biomarkers, such as human kallirein-2, insulinlike growth factor-1 and genetic markers. Future study designs should also consider neural networks to handle the multiple covariates. Finally, with a larger number of patients in each subset and with other cohorts to confirm our findings a nomogram could be constructed to ultimately guide urologists in optimal prostate biopsy management strategies.
Abbreviations and Acronyms DRE ⫽ digital rectal examination FH ⫽ family history HGPIN ⫽ high grade prostatic intraepithelial neoplasia LUTS ⫽ lower urinary tract symptoms PSA ⫽ prostate specific antigen TRUS ⫽ transrectal ultrasonography
REFERENCES 1. Thompson, I. M., Goodman, P. J., Tangen, C. M., Lucia, M. S., Miller, G. J., Ford, L. G. et al: The influence of finasteride on the development of prostate cancer. N Engl J Med, 349: 215, 2003 2. Stamey, T. A., Caldwell, M., McNeal, J. E., Nolley, R., Hemenez, M. and Downs, J.: The prostate specific antigen era in the United States is over for prostate cancer: what happened in the last 20 years? J Urol, 172: 1297, 2004 3. Reiter, R. E. and deKernion, J. B.: Epidemiology, etiology and prevention of prostate cancer. In: Campbell’s Urology, 8th ed. Edited by P. C. Walsh, A. B. Retik, E. D. Vaughan, Jr. and A. J. Wein. Philadelphia: W. B. Saunders Co., vol. 4, sect. XI, chapt. 85, pp. 3001-3016, 2002 4. Narod, S. A., Dupont, A., Cusan, L., Diamond, P., Gomez, J. L., Suburu, R. et al: The impact of family history on early detection of prostate cancer. Nat Med, 1: 99, 1995
5. Catalona, W. J., Southwick, P. C., Slawin, K. M., Partin, A. W., Brawer, M. K., Flanigan, R. C. et al: Comparison of percent free PSA, PSA density, and age-specific PSA cutoffs for prostate cancer detection and staging. Urology, 56: 255, 2000 6. Nam, R. K., Toi, A., Trachtenberg, J., Jewett, M. A., Klotz, L., Fleshner, N. et al: Variation in patterns of practice in diagnosing screen-detected prostate cancer. BJU Int, 94: 1239, 2004 7. Catalona, W. J., Smith, D. S. and Ornstein, D. K.: Prostate cancer detection in men with serum PSA concentrations of 2.6 to 4.0 ng/mL and benign prostate examination. Enhancement of specificity with free PSA measurements. JAMA, 277: 1452, 1997 8. Barry, M. J., Fowler, F. J., Jr., O’Leary, M. P., Bruskewitz, R. C., Holtgrewe, H. L., Mebust, W. K. et al: The American Urological Association symptom index for benign prostatic hyperplasia. The Measurement Committee of the American Urological Association. J. Urol., 148: 1549, 1992 9. Terris, M. K.: Ultrasonography and biopsy of the prostate. In: Campbell’s Urology, 8th ed. Edited by P. C. Walsh, A. B. Retik, E. D. Vaughan, Jr. and A. J. Wein. Philadelphia: W. B. Saunders Co., vol. 4, sect. XI, chapt. 87, pp. 3038-3054, 2002 10. Djavan, B., Ravery, V., Zlotta, A., Dobronski, P., Dobrovits, M., Fakhari, M. et al: Prospective evaluation of prostate cancer detected on biopsies 1, 2, 3 and 4: when should we stop? J Urol, 166: 1679, 2001 11. Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J.: Classification and Regression Trees. Belmont, California: Wadsworth International, 1984 12. Catalona, W. J., Smith, D. S., Ratliff, T. L., Dodds, K. M., Coplen, D. E., Yuan, J. J. J. et al: Measurement of prostatespecific antigen in serum as a screening test for prostate cancer. New Engl J Med, 324: 1156, 1991 13. Matthews, G. J., Motta, J. and Fracehia, J. A.: The accuracy of transrectal ultrasound prostate volume estimation: clinical correlations. J Clin Ultrasound, 24: 501, 1996 14. Ohigashi, T., Kanao, K., Kikuchi, E., Nakagawa, K., Nakashima, J., Marumo, K. et al: Prostate specific antigen adjusted for transition zone epithelial volume: the powerful predictor for the detection of prostate cancer on repeat biopsy. J Urol, 173: 1541, 2005 15. Lopez-Corona, E., Ohori, M., Scardino, P. T., Reuter, V. E., Gonen, M. and Kattan, M. W.: A nomogram for predicting a positive repeat prostate biopsy in patients with a previous negative biopsy session. J Urol, 170: 1184, 2003 16. Nam, R. K., Zhang, W. W., Trachtenberg, J., Diamandis, E. P., Toi, A., Emami, M. et al: Single nucleotide polymorphism of the human kallikrein-2 gene highly correlates with serum human kallikrein-2 levels and in combination enhances prostate cancer detection. J Clin Oncol, 21: 2312, 2003 17. Partin, A. W., Brawer, M. K., Bartsch, G., Horninger, W., Taneja, S. S., Lepor, H. et al: Complexed prostate specific antigen improves specificity for prostate cancer detection: results of a prospective multicenter clinical trial. J Urol, 170: 1787, 2003 18. Kupelian, P. A., Kupelian, V. A., Witte, J. S., Macklis, R. and Klein, E. A.: Family history of prostate cancer in patients with localized prostate cancer: an independent predictor of treatment outcome. J Clin Oncol, 15: 1478, 1997 19. Giovannucci, E., Stampfer, M. J., Krithivas, K., Brown, M., Brufsky, A., Talcott, J. et al: The CAG repeat within the androgen receptor gene and its relationship to prostate cancer. Proc Natl Acad Sci USA, 94: 3320, 1997 20. Wang, L., McDonnell, S. K., Elkins, D. A., Slager, S. L., Christensen, E., Marks, A. F. et al: Analysis of the RNASEL gene in familial and sporadic prostate cancer. Am J Hum Genet, 71: 116, 2002
Purpose: The clinical usefulness of PSA for prostate cancer screening is unclear, although the test remains in common use. New methods to interpret PSA are needed. Materials and Methods: We examined a cohort of 2,637 men who underwent prostate biopsies for abnormal DRE or PSA between 1999 and 2004. Using risk factors for prostate cancer, including patient age, ethnicity, family history of prostate cancer, previous negative biopsy, voiding symptoms and prostate volume, we developed risk groups for prostate cancer using recursive partitioning modeling independent of PSA or DRE. We then compared prostate cancer probabilities by PSA ranges by risk group. Results: Of the 2,637 men 1,282 (48.6%) had prostate cancer. Age, ethnicity, family history, previous negative biopsy and prostate volume were predictive for cancer. We constructed 6 risk groups by combining these factors and created tables to assign patients to these groups. Independent of PSA and DRE the probability of cancer ranged from 15% in patients in group 1 to 78% in patients in group 6 (p ⬍0.0001). By adding PSA and DRE to each risk group prostate cancer probabilities were refined from 0% to 100%. Patients in the higher risk groups also had higher grade cancer (p ⬍0.0001). Conclusions: We generated 6 risk groups based on simple risk factors for prostate cancer. When used in the right context and patient, PSA is highly accurate for predicting prostate cancer and permitting rational decision making in patients with abnormal PSA. Key Words: prostate, prostatic neoplasms, prostate-specific antigen, risk
Several strong risk factors for prostate cancer have been identified, including patient age, ethnic group and a family history of prostate cancer.3,4 Other factors, such as prostate volume and DRE, are also important for determining the risk of prostate cancer.5,6 To our knowledge no study to date has examined in detail how the combination of these risk factors affects the risk of prostate cancer at a given PSA. By establishing different risk profiles in patients based on these factors the risk of prostate cancer could be estimated prior to biopsy and then modified, given a specific PSA. These estimates could aid clinicians and patients in decision making in men faced with abnormal PSA. We examined a cohort of 2,637 patients who underwent 1 or more prostate biopsies in the context of a PSA screening program. We first examined factors that were positively associated with prostate cancer independent of PSA and DRE. Using recursive partitioning modeling we created low to high risk groups for prostate cancer based on a combination of these risk factors for prostate cancer. Finally, estimates of the probability of prostate cancer were modified based on PSA and DRE groupings for each risk group. Using these groupings we were able to dramatically improve our ability to estimate the risk of prostate cancer in an individual for a given PSA and DRE status. Tables were constructed to be able to assign a given patient to these risk groups based on these factors.
t has been questioned whether PSA is an effective screening instrument for prostate cancer management.1,2 Stamey et al argued that the “prostate specific antigen era . . . is over for prostate cancer.”2 This statement was based on studies showing that serum PSA no longer accurately distinguishes patients with prostate cancer from those with benign prostatic hyperplasia at PSA less than 20 ng/ml.2 Another group noted that the prevalence of prostate cancer in men was unexpectedly high (24.4%) in the placebo arm in a randomized study of prostate cancer prevention.1 Thus, there is uncertainty in using PSA as a screening instrument for prostate cancer among decision makers, physicians and patients. Previously established prostate cancer rates in patients with abnormal PSA may not be valid, leading to confusion as to how to interpret PSA. Despite this confusion PSA testing continues to be widely used for prostate cancer screening. Guidelines are needed to interpret the significance of PSA for prostate cancer.
I
Submitted for publication March 22, 2005. Study received hospital research ethics board approval. Supported by National Cancer Institute of Canada Grant 010284, National Cancer Institute of Canada Terry Fox Foundation Grant 015168 and the Canadian Urological Association Scholarship Fund (RKN). * Correspondence: 2075 Bayview Ave., MG-406, Toronto, Ontario, Canada, M4N 3M5 (telephone: 416-480-5075; FAX: 416-480-6121; e-mail: [email protected]).
0022-5347/06/1752-0489/0 THE JOURNAL OF UROLOGY® Copyright © 2006 by AMERICAN UROLOGICAL ASSOCIATION
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Vol. 175, 489-494, February 2006 Printed in U.S.A. DOI:10.1016/S0022-5347(05)00159-X
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METHODS Study subjects. Patients were drawn from a sample of 2,838 eligible men who were referred to the prostate centers at our institution (Sunnybrook and Women’s College Health Sciences Centre, and University Health Network) between June 1999 and June 2004. Patients were included in the study if PSA was greater than 2.5 ng/ml7 or they had abnormal DRE. All patients underwent TRUS and 1 or more prostate biopsies. In Ontario, Canada there are no formal criteria for PSA screening but the practice is widespread. It is important to note that in Canada everyone is insured by a public health insurance system. However, patients eligible for this study were unselected and accrued consecutively. No patient had a history of prostate cancer prior to prostate biopsy. Of the 2,839 men 46 were not capable of providing consent to participate in a research study. Of the remaining 2,793 men 2,637 (94%) consented to participate. All research was performed with informed consent and with the approval of the hospital research ethics board. Baseline data information and primary end point. A urological voiding history (American Urological Association symptom score8), DRE results, serum PSA, family history of prostate cancer information and ethnic background were determined by research personnel through questionnaire administration and all data were stored in a centralized database. Prostate volume was measured by TRUS. Volume was determined by 2 physicians with extensive experience performing TRUS and prostate biopsy (RKN and AT). It was estimated using the formula found to have the best accuracy for prostate volume, that is length in mm ⫻ width in mm ⫻ sagittal height in mm ⫻ 0.0005236 ⫽ volume in cc,9 where length and height are measured on the mid sagittal view and width is measured on the on transverse axial view. Six to 15 ultrasound guided needle core biopsies (median 8) were performed using an 18 gauge spring loaded biopsy device. Samples were obtained using a systematic pattern and additional targeted samples were obtained from suspicious areas. The primary end point was the histological presence of adenocarcinoma of the prostate in the biopsy specimen. All grading was based on the Gleason scoring system. All histological interpretations were interpreted by 2 experienced genitourinary pathologists (LS and JS). We6 and others10 have reported that approximately 15% to 30% of patients have cancer on repeat prostate biopsy after an initial negative biopsy. Therefore, patients who had an initial negative biopsy were offered repeat prostate biopsies. Of the 2,637 patients 1,166 (44.2%) had cancer. Of the remaining 1,471 men who did not have cancer 408 underwent 1 or more repeat prostate biopsies, of whom 116 (28.4%) had cancer. We did not consider men who underwent more than 1 repeat biopsy after previous negative biopsies as a separate variable due to small sample size (69) and they were grouped with the 408 patients. Of the 2,637 patients 1,282 (48.6%) had cancer (cases) and 1,355 (51.4%) had no evidence of cancer (controls). Data analysis. Cases were defined as patients with adenocarcinoma of the prostate on any biopsy and controls were defined as having no evidence of cancer on any biopsy. Potential factors associated with increased prostate cancer risk were compared between cases and controls, including age,
ethnicity, family history of prostate cancer, prostate volume, LUTS, PSA and DRE. We did not consider the number of needle cores obtained as a potential predictor because we have previously observed that it is not a predictor for prostate cancer.6 Unconditional logistic regression analysis was used to estimate the OR for prostate cancer detection for each of these factors alone and in combination. To improve the positive predictive value for prostate cancer detection by PSA and DRE results we created risk groups by factors that we have found are associated with prostate cancer, including age, ethnicity, family history of prostate cancer, prostate volume and LUTS, as described.3,4 We also considered whether a patient had a previous negative biopsy. Using these risk groups we estimated the risk of prostate cancer according to PSA and DRE result. We created specific tables to show how the combination of factors affects the risk of prostate cancer in a given patient. Creation of risk groups. To derive risk groups for prostate cancer we divided the 2,637 patients into 2 separate data sets (at random) to create an analysis data set comprising of 2,100 (80%) and a validation data set of 537 (20%). Patients included in the analysis data set were used to construct risk groups based on the demographic and clinical predictors. The accuracy of the risk groups proposed using the analysis data set were then evaluated using the validation data set. To determine whether correct assignments to risk groups were made the probability of prostate cancer by each risk group was compared between the analysis and validation data sets. We used recursive partitioning analysis to create a classification tree for modeling predictor variables.11 Predictor variables were age at biopsy, ethnicity, family history of prostate cancer, previous negative biopsy, prostate volume and LUTS. The data were successively split according to each possible binary grouping of patients and nodes were defined by which the split created 2 groups of patients with the maximally distinguishable difference in the outcome variable, ie cancer. Splitting was stopped when any branch contained fewer than 30 patients. Statistical significance was defined as p ⬍0.05. Branches were tested for differences using the 2-sided chi-square test, adjusting for multiple comparisons (significance at Bonferroni corrected p ⫽ 0.0028). The additional information provided by DRE and PSA testing was evaluated in each proposed risk group using the Cochran-Armitage test for trend. Correlations with histological grade were also investigated. We categorized age at biopsy by decades and prostate volume by its quartile distribution. RESULTS Mean age at biopsy in the 2,637 men was 64.8 years (range 39.9 to 93.8). Mean PSA was 10.8 ng/ml (median 7.28, range 0.05 to 498.8), while 38.4% of the men had abnormal DRE. The majority of the patients were white (2,181 or 82.7%), while 253 (9.6%) and 133 (5.0%) were black and Asian, respectively. Of the patients 13% had at least 1 relative with prostate cancer. Of the 2,637 men 1,282 (48.6%) were found to have adenocarcinoma of the prostate at biopsy (cases) in 1 or more biopsies and 1,355 (51.4%) had no evidence of cancer (controls). Of the 1,282 men with cancer 24 (1.9%), 531 (41.4%),
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TABLE 1. Prostate cancer factors in cases and controls, and multivariate analysis of factors related to prostate cancer Factor No. Subjects (%)
Ca 1,282 (48.6)
No Ca 1,355 (51.4)
p Value
Adjusted OR* (95% CI)
p Value
Mean age ⫾ SD No. family history (%): Absent Present No. ethnicity (%): Asian White Black Other LUTS: Absent Present Median cc prostate vol (range) No. DRE (%): No nodule Nodule Median ng/ml PSA (range) No. previous neg biopsy (%): No Yes
66.0 ⫾ 8.5
63.6 ⫾ 8.1
⬍0.0001
1.05† (1.03–1.05)
⬍0.0001
1,083 (47.5) 199 (56.1)
1,199 (52.5) 156 (43.9)
0.003
39 (29.3) 1,072 (49.2) 144 (56.9) 27 (38.6)
94 (70.6) 1,109 (50.8) 109 (43.1) 43 (61.4)
⬍0.0001
774 (51.3) 508 (45.0) 47.0 (15–295)
734 (48.7) 621 (55.0) 61.0 (15–295)
943 (45.3) 339 (61.0) 7.85 (0.6–498.8) 1,166 (52.3) 116 (28.4)
0.001 ⬍0.0001
1,138 (54.7) 217 (39.0) 6.76 (0.05–132.4)
⬍0.0001
1,063 (47.7) 292 (71.6)
⬍0.0001
⬍0.0001
1.00 1.41 (1.1–1.8)
0.007
1.00‡ 2.49 (1.8–3.5) 3.75 (2.4–5.7)
⬍0.0001 ⬍0.0001
1.00 0.86 (0.7–1.0) 0.98† (0.97–0.99)
0.09 ⬍0.0001
1.00 1.48 (1.2–1.8) 1.07† (1.05–1.08)
0.0003 ⬍0.0001
1.00 0.45 (0.4–0.6)
⬍0.0001
* Multivariate model includes age at biopsy, family history of prostate cancer, ethnicity, LUTS, prostate volume, DRE, PSA and previous negative biopsy. † Age at biopsy per year, prostate volume per cc and PSA/ng/ml considered continuous variables in the multivariate model. ‡ Baseline group defined as Asian and other.
565 (44.1%) and 162 (12.6%) had Gleason score 4 or 5, 6, 7 and 8 to 10, respectively. All risk factors for prostate cancer were found to be significantly associated with prostate cancer (table 1). On multivariate analysis all factors were independently associated with prostate cancer risk (table 1). In particular patients who had an initial negative biopsy were at a lower risk for prostate cancer at repeat biopsy (adjusted OR 0.45, p ⫽ 0.0001). Results of classification tree for risk factors for prostate cancer without PSA or DRE. Of the 2,637 patients 2,100 were placed in the analysis data set and 537 were in the validation data set. There were no significant differences in baseline characteristics between the 2 groups with respect to age, ethnicity, family history of prostate cancer, prostate volume, LUTS, PSA and DRE (data not shown). In the recursive model 6 distinct groups of combinations of risk factors for prostate cancer were created from the classification tree. Age, ethnicity, family history of prostate cancer, prostate volume and previous negative biopsy were important factors for determining the groupings. Only LUTS did not contribute independent information in the recursive model. Multiple combinations of these factors determined and categorized into the 6 distinct risk groups from the recursive model showed significant differences in prostate cancer risk
across the groups (p ⬍0.0001, table 2). Group 1 had the lowest percent prostate cancer risk (14.9%) and group 6 had the highest prostate cancer risk (78.2%). Table 3 shows how the combinations of risk factors were assigned by the model to each of the 6 groups in all patients. Using table 3 a risk group category can be assigned based on the age, ethnicity, family history of prostate cancer, previous negative biopsy and prostate volume in an individual. When applied to patients in the validation data set, the results were similar (table 2). We also examined whether the risk groups were predictive for prostate cancer after adjusting for DRE and PSA in a multivariate model. The adjusted OR for prostate cancer in patients in groups 6 to 2 were 31.8 (95% CI 17.2 to 58.7, p ⬍0.0001), 19.3 (95% CI 10.3 to 36.0, p ⬍0.0001), 11.0 (95% CI 6.1 to 19.6, p ⬍0.0001), 4.74 (95% CI 2.7 to 8.5, p ⬍0.0001) and 3.28 (95% CI 1.8 to 5.8, p ⬍0.0001), respectively, when using group 1 as the baseline group. To determine whether the groupings predicted patients who had aggressive prostate cancer we compared the distribution of histological grade at diagnosis among the risk groups regardless of PSA or DRE. The 6 risk factor groups were significantly associated with grade at diagnosis. Patients in the lowest risk group had a lower proportion of high grade (Gleason score 7 or more) cancers than patients in the highest risk group (0% vs 71.4%, p ⬍0.0001, table 4).
TABLE 2. Probability of cancer by risk group with comparison between analysis and validation data sets Analysis Data Set Group
% Prostate Ca Risk (No. pts)*
1 2 3 4 5 6
14.9 (13) 29.6 (189) 42.8 (171) 56.1 (262) 66.0 (126) 78.2 (247)
Validation Data Set No. Pts
% Prostate Ca Risk (No. pts)
95% CI
No. Pts
87 639 400 467 191 316
8.0 (2) 34.3 (57) 39.6 (38) 60.7 (71) 70.4 (38) 86.1 (68)
(1.0–26.0) (27.2–42.1) (29.7–50.1) (51.2–69.6) (56.4–82.0) (76.5–92.8)
25 166 96 117 54 79
* For 2 ⫻ 6 table comparing cancer vs controls across the 6 risk groups chi-square 371.7, p ⬍0.0001.
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TABLE 3. Patient grouping by risk factors for prostate cancer independent of PSA or DRE, as determined by recursive partitioning model Prostate Vol (cc) Age White, no previous biopsy: Younger than 50 50–60 60–70 Older than 70 Black, no previous biopsy: Younger than 50 50–60 60–70 Older than 70 Asian/other, no previous biopsy: Younger than 50 50–60 60–70 Older than 70 Initial neg biopsy, any ethnic background: Younger than 50 50–60 60–70 70 or Older
Less Than 40
40–55
55–75
75 or Greater
2 4 5 6
2 4 4 (neg FH), 5 (pos FH) 6
2 3,5 3 (neg FH), 5 (pos FH) 4
2 2 2 3
2 6 6 6
2 6 6 6
2 3 (neg FH), 5 (pos FH) 3 (neg FH), 5 (pos FH) 4
2 2 2 3
2 2 2 6
2 2 2 6
2 2 2 4
2 2 2 3
2 2 2 2
2 2 2 2
2 2 2 2
1 1 1 3
Using this table a patient can be assigned to group 1 to 6 according to age, prostate volume, ethnicity, prostate cancer family history and whether previous initial biopsy was negative.
Probability of prostate cancer by PSA and DRE based on risk groups. We calculated the probability of prostate cancer by PSA and DRE status in patients in each of the 6 risk groups (table 5). To increase study power we combined the analysis and validation data sets. For each PSA category the probability of cancer varied widely among risk groups. For PSA 0 to 3.99 ng/ml the probability increased from 0% to 55.6% depending on the risk group, for 4.0 to 9.99 ng/ml the probability increased from 11.1% to 90.9% depending on the risk group, for 10.0 to 19.99 ng/ml the probability increased from 3.3% to 92.6% depending on the risk group and for values greater than 20.0 ng/ml the probability increased from 0% to 100% depending on the risk group. PSA categories were also able to further distinguish grade at diagnosis. DISCUSSION We provide a clinical instrument for physicians to help determine the risk of prostate cancer in a patient with abnormal PSA or DRE. Using table 3 physicians will be able to determine the risk group of the patient and estimate his underlying risk of prostate cancer and the likelihood of an aggressive form of cancer. Using table 5 a specific probability for prostate cancer can be determined based on PSA and DRE status. These estimates will allow more informed decision making by physicians and patients when considering prostate biopsies, particularly when aggressive forms of
prostate cancer can be predicted. However, it is important to note that these results apply to men with abnormal PSA or DRE, in contrast to a general screening population. To illustrate this, in large cohort and screening studies the probability of prostate cancer in patients with PSA 4.0 to 10.0 ng/ml is 30% to 50%.10,12 These intermediate estimates make it difficult to interpret the risk of prostate cancer in a patient. From our study we can now provide a better estimate of the risk of prostate cancer in patients who are in this range. Specifically in patients with normal DRE and PSA 4.0 to 10.0 ng/ml the risk is 15%, 30%, 40%, 57%, 67% and 75% in groups 1 to 6, respectively. In patients with abnormal DRE the risk ranges from 11% in group 1 to 91% in group 6. Furthermore, the risk of high grade cancer in this PSA range is highest in groups 3 to 6. With these refined probabilities for prostate cancer based on PSA and DRE using these risk groups biopsy management strategies can be improved. For example, in patients at 90% or more risk for prostate cancer with an initial negative biopsy repeat biopsy would be clearly indicated, particularly when the odds of having high grade cancer are found to be high based on risk group and PSA. Also, patients with normal PSA (less than 4 ng/ml) but in a high risk group (5 or 6) should undergo biopsy, given a probability of up to 50% for prostate cancer and the increased likelihood of high grade disease based on risk group alone. On the other hand, pa-
TABLE 4. Histological grade by risk group
Group
% Prostate Ca* Risk (No./total No.)
1 2 3 4 5 6
13.4 (15/112) 30.6 (246/805) 42.1 (209/496) 57.0 (333/584) 66.9 (164/245) 79.7 (315/395)
No. Gleason Score
(%)†
Low
High
High/Low
15 (100.0) 167 (68.9) 89 (42.6) 129 (38.7) 65 (39.6) 90 (28.6)
0 79 (32.1) 120 (57.4) 204 (61.3) 99 (60.4) 225 (71.4)
0/1 0.5/1 1.3/1 1.6/1 1.5/1 2.5/1
* Based on combined analysis and validation dataset groups (2,637 patients). † Distribution of Gleason scores 4 to 6 (low) vs 7 to 10 (high) across 6 risk groups 2 ⫻ 6 table chi-square 111.8. (p ⬍ 0.0001).
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TABLE 5. Cancer probability according to risk group by PSA in patients with normal and abnormal DRE % PSA (No./total No.) Group Normal: 1 2 3 4 5 6 Abnormal: 1 2 3 4 5 6
0–3.9 Ng/Ml
4.0–9.9 Ng/Ml
10.0–19.9 Ng/Ml
Greater Than 20.0 Ng/Ml
p Value
50.0 (1/2) 14.3 (7/49) 5.6 (1/18) 23.4 (15/64) 25.8 (8/31) 51.9 (14/27)
15.3 (9/59) 29.8 (128/430) 39.5 (92/233) 57.3 (153/267) 66.7 (76/114) 75.2 (109/145)
3.3 (1/30) 34.1 (61/179) 44.2 (46/104) 60.8 (48/79) 85.3 (29/34) 83.1 (49/59)
14.3 (1/7) 54.1 (20/37) 39.5 (17/43) 73.3 (22/30) 71.4 (5/7) 93.9 (31/33)
0.17 ⬍0.001 0.06 ⬍0.001 ⬍0.001 ⬍0.001
0.0 2.5 (1/40) 16.7 (2/12) 18.4 (7/38) 40.0 (6/15) 55.6 (15/27)
11.1 (1/9) 34.7 (17/49) 53.6 (30/56) 80.8 (59/73) 91.7 (33/36) 90.9 (50/55)
40.0 (2/5) 47.1 (8/17) 57.9 (11/19) 87.0 (20/23) 83.3 (5/6) 92.6 (25/27)
0.0 39.5 (4/4) 90.0 (10/11) 90.0 (9/10) 100.0 (2/2) 100.0 (22/22)
0.51 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001
tients at less than 15% risk for prostate cancer may consider not undergoing biopsy, particularly if they are in a risk group and at a PSA where there is a high chance of low grade disease. Also, the prevalence of prostate cancer may be as high as 15% in patients with normal PSA based on the Prostate Cancer Prevention Study.1 The concept of using risk factors for prostate cancer to interpret the significance of abnormal PSA is not new. However, to our knowledge no group has estimated the precise risk of prostate cancer based on combining these multiple factors in a clinical setting. Narod et al were the first to estimate the risk of prostate cancer based on a family history of prostate cancer in a large screening study but they not consider other risk factors.4 Although age and prostate volume have been considered individually to adjust PSA,5 no clinically accepted standard has been created. A possible reason may be due to the variability in interpreting prostate volume on ultrasonography.13 This would be an important issue to consider in our study since prostate volume was an important predictor. However, the quartile cutoffs are within reported measurement error limits and a higher degree of volume measurement error primarily occurs with large prostates, that is beyond 75 cc,13 which was our fourth quartile. Furthermore, our data clearly show that multiple factors, including ethnic background and family history of prostate cancer, are important when estimating the risk of prostate cancer with PSA and DRE. Another consideration is that prostate volume assessment will be required prior to biopsy to estimate the risk of prostate cancer. Although transrectal ultrasound alone has not been used as a single diagnostic test, it would be required to obtain an accurate prostate volume measurement. However, other, less invasive imaging techniques could be used to estimate prostate volume. Another consideration is the measurement of transition zone volume. Ohigashi et al recently reported that transition zone epithelial volume independently predicted prostate cancer in patients with PSA 4.0 to 10.0 ng/ml.14 A limitation of this study is that transition zone volumes were not measured. Future confirmatory studies should also consider transition zone volume to refine the risk groupings. Stamey et al examined 1,317 patients who underwent surgery and compared PSA with respect to the volume of prostate cancer and benign prostatic hyperplasia tissue.2 They concluded that PSA (less than 20 ng/ml) was only related to the amount of benign prostate tissue present.
However, they did not compare these patients to normal controls and did not consider how other prostate cancer risk factors could have affected their analysis. Also, in the Prostate Cancer Prevention Study Thompson et al reported a 24.4% prevalence of prostate cancer in 4,692 men in the placebo arm.1 However, they also did not stratify by other risk factors for prostate cancer when reporting cancer prevalence rates. We acknowledge that some estimates of prostate cancer risk did not show a significant trend by PSA categories. In some subgroups this may have been due to lack of sample size in each subgroup, particularly in patients in group 1. However, in this group it may be possible that PSA is not predictive of prostate cancer, although Group 1 only consisted of 4% of the study population (102 of 2,637 men). Patients in group 1 were those with a previous negative biopsy, prostate volume 75 cc or greater and age less than 70 years. We6 and others15 have reported that in patients who undergo repeat biopsy after negative initial biopsy PSA is not an important predictor of prostate cancer. It is important to consider whether patients had an initial negative biopsy in the recursive model, given the 15% to 30% prevalence of prostate cancer after repeat biopsy.6,10 Cancer lesions may be missed on initial biopsy due to sampling error. Thus, the prediction model had to consider whether a patient had had a previous negative biopsy, given that it could affect the risk of prostate cancer. Although not all patients underwent repeat biopsy after an initial negative biopsy, the majority of repeat biopsies were done because of persistent abnormal PSA or HGPIN.6 We did not consider HGPIN separately in the model since a primary indication for repeat biopsy was HGPIN. Including a HGPIN variable and a previous negative biopsy variable would have resulted in co-linearity in the regression model (table 1). Thus, only 1 variable was used. We16 and others17 have examined other biomarkers, including free and complexed PSA, and human kallirein-2, but their additional predictive value was not significantly better for all levels of total PSA. Of these biomarkers only the free-to-total PSA ratio provided additional predictive information for PSA 4.0 to 10.0 ng/ml.5 However, to our knowledge no standard cutoffs for the free-to-total PSA ratio have been established. None have been able to significantly distinguish low and high grade cancers, which we were able to do based on risk factors alone. Finally, the role of free-to-
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total PSA is limited to patients with total PSA less than 10 ng/ml. The observation that risk groups were significantly associated with grade at diagnosis was unexpected. To our knowledge this association has not been described previously. Particularly in group 6 patients were at a greater than 2-fold increased risk for high vs low grade cancer (table 4). When we examined any possible correlations with the factors individually with grade, no single factor was found to be significantly associated with grade (data not shown). However, in combination patients in higher risk groups were found to be at higher risk for high grade cancer. It is possible that a family history of prostate cancer may be an important factor in this association. Kupelian et al observed that a family history of prostate cancer may indicate a worse prognosis in patients with localized disease compared to patients without a family history of cancer.18 It is likely that patients have a genetic predisposition toward aggressive or nonaggressive prostate cancer. Polymorphisms of various candidate genes have been associated with advanced prostate cancer.19 Mutations of RNAsel, the putative gene for HPC1 found by linkage, have also been implicated in an association with advanced prostate cancer.20 Subsequent prediction models should be extended to include new biomarkers, such as human kallirein-2, insulinlike growth factor-1 and genetic markers. Future study designs should also consider neural networks to handle the multiple covariates. Finally, with a larger number of patients in each subset and with other cohorts to confirm our findings a nomogram could be constructed to ultimately guide urologists in optimal prostate biopsy management strategies.
Abbreviations and Acronyms DRE ⫽ digital rectal examination FH ⫽ family history HGPIN ⫽ high grade prostatic intraepithelial neoplasia LUTS ⫽ lower urinary tract symptoms PSA ⫽ prostate specific antigen TRUS ⫽ transrectal ultrasonography
REFERENCES 1. Thompson, I. M., Goodman, P. J., Tangen, C. M., Lucia, M. S., Miller, G. J., Ford, L. G. et al: The influence of finasteride on the development of prostate cancer. N Engl J Med, 349: 215, 2003 2. Stamey, T. A., Caldwell, M., McNeal, J. E., Nolley, R., Hemenez, M. and Downs, J.: The prostate specific antigen era in the United States is over for prostate cancer: what happened in the last 20 years? J Urol, 172: 1297, 2004 3. Reiter, R. E. and deKernion, J. B.: Epidemiology, etiology and prevention of prostate cancer. In: Campbell’s Urology, 8th ed. Edited by P. C. Walsh, A. B. Retik, E. D. Vaughan, Jr. and A. J. Wein. Philadelphia: W. B. Saunders Co., vol. 4, sect. XI, chapt. 85, pp. 3001-3016, 2002 4. Narod, S. A., Dupont, A., Cusan, L., Diamond, P., Gomez, J. L., Suburu, R. et al: The impact of family history on early detection of prostate cancer. Nat Med, 1: 99, 1995
5. Catalona, W. J., Southwick, P. C., Slawin, K. M., Partin, A. W., Brawer, M. K., Flanigan, R. C. et al: Comparison of percent free PSA, PSA density, and age-specific PSA cutoffs for prostate cancer detection and staging. Urology, 56: 255, 2000 6. Nam, R. K., Toi, A., Trachtenberg, J., Jewett, M. A., Klotz, L., Fleshner, N. et al: Variation in patterns of practice in diagnosing screen-detected prostate cancer. BJU Int, 94: 1239, 2004 7. Catalona, W. J., Smith, D. S. and Ornstein, D. K.: Prostate cancer detection in men with serum PSA concentrations of 2.6 to 4.0 ng/mL and benign prostate examination. Enhancement of specificity with free PSA measurements. JAMA, 277: 1452, 1997 8. Barry, M. J., Fowler, F. J., Jr., O’Leary, M. P., Bruskewitz, R. C., Holtgrewe, H. L., Mebust, W. K. et al: The American Urological Association symptom index for benign prostatic hyperplasia. The Measurement Committee of the American Urological Association. J. Urol., 148: 1549, 1992 9. Terris, M. K.: Ultrasonography and biopsy of the prostate. In: Campbell’s Urology, 8th ed. Edited by P. C. Walsh, A. B. Retik, E. D. Vaughan, Jr. and A. J. Wein. Philadelphia: W. B. Saunders Co., vol. 4, sect. XI, chapt. 87, pp. 3038-3054, 2002 10. Djavan, B., Ravery, V., Zlotta, A., Dobronski, P., Dobrovits, M., Fakhari, M. et al: Prospective evaluation of prostate cancer detected on biopsies 1, 2, 3 and 4: when should we stop? J Urol, 166: 1679, 2001 11. Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J.: Classification and Regression Trees. Belmont, California: Wadsworth International, 1984 12. Catalona, W. J., Smith, D. S., Ratliff, T. L., Dodds, K. M., Coplen, D. E., Yuan, J. J. J. et al: Measurement of prostatespecific antigen in serum as a screening test for prostate cancer. New Engl J Med, 324: 1156, 1991 13. Matthews, G. J., Motta, J. and Fracehia, J. A.: The accuracy of transrectal ultrasound prostate volume estimation: clinical correlations. J Clin Ultrasound, 24: 501, 1996 14. Ohigashi, T., Kanao, K., Kikuchi, E., Nakagawa, K., Nakashima, J., Marumo, K. et al: Prostate specific antigen adjusted for transition zone epithelial volume: the powerful predictor for the detection of prostate cancer on repeat biopsy. J Urol, 173: 1541, 2005 15. Lopez-Corona, E., Ohori, M., Scardino, P. T., Reuter, V. E., Gonen, M. and Kattan, M. W.: A nomogram for predicting a positive repeat prostate biopsy in patients with a previous negative biopsy session. J Urol, 170: 1184, 2003 16. Nam, R. K., Zhang, W. W., Trachtenberg, J., Diamandis, E. P., Toi, A., Emami, M. et al: Single nucleotide polymorphism of the human kallikrein-2 gene highly correlates with serum human kallikrein-2 levels and in combination enhances prostate cancer detection. J Clin Oncol, 21: 2312, 2003 17. Partin, A. W., Brawer, M. K., Bartsch, G., Horninger, W., Taneja, S. S., Lepor, H. et al: Complexed prostate specific antigen improves specificity for prostate cancer detection: results of a prospective multicenter clinical trial. J Urol, 170: 1787, 2003 18. Kupelian, P. A., Kupelian, V. A., Witte, J. S., Macklis, R. and Klein, E. A.: Family history of prostate cancer in patients with localized prostate cancer: an independent predictor of treatment outcome. J Clin Oncol, 15: 1478, 1997 19. Giovannucci, E., Stampfer, M. J., Krithivas, K., Brown, M., Brufsky, A., Talcott, J. et al: The CAG repeat within the androgen receptor gene and its relationship to prostate cancer. Proc Natl Acad Sci USA, 94: 3320, 1997 20. Wang, L., McDonnell, S. K., Elkins, D. A., Slager, S. L., Christensen, E., Marks, A. F. et al: Analysis of the RNASEL gene in familial and sporadic prostate cancer. Am J Hum Genet, 71: 116, 2002