Although acupuncture is widely used for chronic pain, there remains considerable controversy as to its value. We aimed to determine the effect size of acupuncture for four chronic pain conditions: back and neck pain, osteoarthritis, chronic headache, and shoulder pain.
We conducted a systematic review to identify randomized trials of acupuncture for chronic pain where allocation concealment was determined unambiguously to be adequate. Individual patient data meta-analyses were conducted using data from 29 of 31 eligible trials, with a total of 17,922 patients analyzed.
In the primary analysis including all eligible trials, acupuncture was superior to both sham and no acupuncture control for each pain condition (all p<0.001). After exclusion of an outlying set of trials that strongly favored acupuncture, the effect sizes were similar across pain conditions. Patients receiving acupuncture had less pain, with scores 0.23 (95% C.I. 0.13, 0.33), 0.16 (95% C.I. 0.07, 0.25) and 0.15 (95% C.I. 0.07, 0.24) standard deviations lower than sham controls for back and neck pain, osteoarthritis, and chronic headache respectively; the effect sizes in comparison to no acupuncture controls were 0.55 (95% C.I. 0.51, 0.58), 0.57 (95% C.I. 0.50, 0.64) and 0.42 (95% C.I. 0.37, 0.46). These results were robust to a variety of sensitivity analyses, including those related to publication bias.
Acupuncture is effective for the treatment of chronic pain and is therefore a reasonable referral option. Significant differences between true and sham acupuncture indicate that acupuncture is more than a placebo. However, these differences are relatively modest, suggesting that factors in addition to the specific effects of needling are important contributors to the therapeutic effects of acupuncture.
To assess the applicability of the Prostate Cancer Prevention Trial High Grade (Gleason grade ≥ 7) Risk Calculator (PCPTHG) in ten international cohorts, representing a range of populations.
25,512 biopsies from 10 cohorts (6 European, 1 UK, and 3 US) were included; 4 implemented 6-core biopsies and the remaining had 10- or higher schemes; 8 were screening cohorts and 2 were clinical. PCPTHG risks were calculated using prostate-specific antigen (PSA), digital rectal examination, age, African origin and history of prior biopsy and evaluated in terms of calibration plots, areas underneath the receiver operating characteristic curve (AUC), and net benefit curves.
The median AUC of the PCPTHG for high grade disease detection in the 10- and higher-core cohorts was 73.5% (range 63.9% to 76.7%) compared to a median of 78.1 (range = 72.0 to 87.6) among the four 6-core cohorts. Only the 10-core Cleveland Clinic cohort showed clear evidence of under-prediction by the PCPTHG, and this was restricted to risk ranges less than 15%. The PCPTHG demonstrated higher clinical net benefit in higher- compared to six-core biopsy cohorts, and among the former, there were no notable differences observed between clinical and screening cohorts, nor between European and US cohorts.
The PCPTHG requires minimal patient information and can be applied across a range of populations. PCPTHG risk thresholds ranging from 5 to 20%, depending on patient risk averseness, are recommended for clinical prostate biopsy decision-making.
Calibration; Discrimination; Net Benefit; High Grade Prostate Cancer; Risk; Prostate Cancer Prevention Trial
Prostate cancer is a heterogenous disease with a variable natural history that is not accurately predicted by currently used prognostic tools.
We genotyped 798 prostate cancer cases of Ashkenazi Jewish ancestry treated for localized prostate cancer between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to clinical data. The survival analysis was adjusted for Gleason score and PSA. We investigated associations between 29 single nucleotide polymorphisms (SNPs) and biochemical recurrence, castration-resistant metastasis, and prostate cancer-specific survival. Subsequently, we performed an independent analysis using a high resolution panel of 13 SNPs.
On univariate analysis, 2 SNPs were associated (p<0.05) with biochemical recurrence; 3 SNPs were associated with clinical metastases; and 1 SNP was associated with prostate cancer-specific mortality. Applying a Bonferroni correction (p<0.0017), one association with biochemical recurrence (p=0.0007) was significant. Three SNPs showed associations on multivariable analysis, although not after correcting for multiple testing. The secondary analysis identified an additional association with prostate cancer-specific mortality in KLK3 (p<0.0005 by both univariate and multivariable analysis).
We identified associations between prostate cancer susceptibility SNPs and clinical endpoints. The rs61752561 in KLK3 and rs2735839 in the KLK2-KLK3 intergenic region associated strongly with prostate cancer-specific survival, and rs10486567 in 7JAZF1 gene associated with biochemical recurrence. A larger study will be required to independently validate these findings and determine the role of these SNPs in prognostic models.
Single nucleotide polymorphisms; Prostate cancer; Prognosis
Following the multidisciplinary management of metastatic germ cell tumor, approximately 10 to 15% of patients with the histologic finding of fibrosis or teratoma will suffer disease recurrence. We evaluated the prognostic significance of the total number of lymph nodes obtained at post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND).
Materials and Methods
From 1989 to 2006, a total of 628 patients underwent PC-RPLND and were found to have either fibrosis or teratoma. Following Institutional Review Board approval, complete clinical and pathologic data were obtained from our prospective testis cancer surgical database. A Cox proportional hazards regression model was constructed to evaluate the association of the total number of lymph nodes obtained at PC-RPLND on disease recurrence.
On pathologic evaluation, 248 (57%) patients had fibrosis and 184 (43%) patients had teratoma. The median number of lymph nodes resected was 25 (IQ range 15, 37). On multivariable analysis, increasing post-chemotherapy nodal size and decreasing lymph node counts were significant predictors of disease recurrence (p=0.01, 0.04, respectively). For patients with 10 nodes removed, the predicted 2 year relapse free probability was 90%, compared to 97% when 50 nodes were removed.
Our data suggests that the total number of lymph nodes removed and analyzed is an independent predictor of disease recurrence following PC-RPLND. This has implications both for the urologist to assure completeness of resection and for the pathologist to meticulously assess the pathologic specimens.
testis cancer; surgery; chemotherapy; lymph node count
Focal treatment is a curative option for localized prostate cancer (PCA), but appropriate selection of patients hasn’t been established. We analyzed patients who had undergone radical prostatectomy (RP), with preoperative disease features considered favorable for focal treatment, to test the hypothesis that they would be accurately characterized with transrectal biopsy and prostate MRI.
202 patients with PCA who had preoperative MRI and low-risk biopsy criteria (no Gleason grade 4/5, one involved core, < 2 mm, PSA density ≤ 0.10, clinical stage ≤ T2a). Indolent RP pathology was defined as no Gleason 4/5, organ confined, tumor volume < 0.5cc, negative surgical margins. MRI ability to locate and determine the tumor extent was assessed.
After RP, 101 men (50%) had non-indolent cancer. Multifocal and bilateral tumors were present in 81% and 68% of patients, respectively. MRI indicated extensive disease in 16 (8%). MRI sensitivity to locate PCA ranged from 2–20%, and specificity from 91–95%. On univariate analysis, MRI evidence of extracapsular extension (ECE) (P = 0.027) and extensive disease (P = 0.001) were associated with non-indolent cancer. On multivariate analysis, only the later remained as significant predictor (P = 0.0018).
Transrectal biopsy identified men with indolent tumors favorable for focal treatment in 50% of cases. MRI findings of ECE and extensive tumor involving more than half of the gland are associated with unfavorable features, and may be useful excluding patients from focal treatment. According to these data, endorectal MRI isn’t sufficient to localize small tumors for focal treatment.
Focal therapy; Prostate biopsy; Prostate cancer; Prostate MRI
To evaluate the discrimination, calibration and net benefit performance of the Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) across five European Randomized study of Screening for Prostate Cancer (ERSPC), 1 United Kingdom, 1 Austrian and 3 US biopsy cohorts.
PCPTRC risks were calculated for 25,733 biopsies using prostate-specific antigen (PSA), digital rectal examination, family history and history of prior biopsy, and single imputation for missing covariates. Predictions were evaluated using the areas underneath the receiver operating characteristic curves (AUC), discrimination slopes, chi-square tests of goodness of fit, and net benefit decision curves.
AUCs of the PCPTRC ranged from a low of 56% in the ERSPC Goeteborg Rounds 2-6 cohort to a high of 72% in the ERSPC Goeteborg Round 1 cohort, and were statistically significantly higher than that of PSA in 6 out of the 10 cohorts. The PCPTRC was well-calibrated in the SABOR, Tyrol and Durham cohorts. There was limited to no net benefit to using the PCPTRC for biopsy referral compared to biopsying all or no men in all five ERSPC cohorts and benefit within a limited range of risk thresholds in all other cohorts.
External validation of the PCPTRC across ten cohorts revealed varying degree of success highly dependent on the cohort, most likely due to different criteria for and work-up before biopsy. Future validation studies of new calculators for prostate cancer should acknowledge the potential impact of the specific cohort studied when reporting successful versus failed validation.
receiver operating characteristic curve; risk; prostate cancer; calibration; net benefit
To assess variation of total prostate-specific antigen (tPSA), free PSA (fPSA), percent fPSA, human glandular kallikrein 2 (hK2), and intact PSA measured three times within two weeks. Knowledge of the variation in an individual’s PSA level is important for clinical decision-making.
Patients and Methods
Study participants were 149 patients referred for prostate biopsy, of which 97 had benign disease and 52 had prostate cancer. Three blood samples were drawn with a median of four hours between first and second samples and 12 days between first and third samples. Variability was described by absolute differences, ratios and intra-individual coefficients of variation. Total PSA, fPSA, hK2, and intact PSA were measured in anti-coagulated blood plasma.
At baseline, the median tPSA was 6.8 (IQR 4.5, 9.6) ng/mL. The intra-individual variation was low for all biomarkers, and lowest for tPSA. For 80% of participants, the ratio between first and second time points for tPSA was between 0.91 and 1.09 and the ratio for percent fPSA was between 0.89 and 1.15. Total coefficients of variation between time 1 and 2 for tPSA, fPSA, percent fPSA, hK2 and intact PSA were 4.0%, 6.6%, 6.0%, 9.2%, and 9.5%, respectively. The measurements taken several days apart varied more than those taken on the same day, but the variation between both time points were not large.
The intra-individual variation for all the kallikrein-like markers studied was relatively small, especially for samples drawn the same day. Few cases are reclassified between the time points. This indicates high short-term biological and technical reproducibility of the tests in clinical use.
Free PSA; Prostate cancer; PSA; Screening; Variation
Prostate specific antigen (PSA) velocity has been proposed as a marker to aid detection of prostate cancer. We sought to determine whether PSA velocity could predict the results of repeat biopsy in men with persistently elevated PSA after initial negative biopsy.
Materials and Methods
We identified 1,837 men who participated in the Göteborg or Rotterdam section of the European Randomized Screening study of Prostate Cancer (ERSPC), and who had one or more subsequent prostate biopsies after an initial negative finding. We evaluated whether PSA velocity improved predictive accuracy beyond that of PSA alone.
There were a total of 2579 repeat biopsies, of which 363 (14%) were positive for prostate cancer, and 44 (1.7%) were high grade (Gleason score ≥7). Although PSA velocity was statistically associated with cancer risk (p<0.001), it had very low predictive accuracy (area-under-the-curve [AUC] of 0.55). There was some evidence that PSA velocity improved AUC compared to PSA for high grade cancer. However, the small increase in risk associated with high PSA velocity – from 1.7 % to 2.8% as velocity increased from 0 to 1 ng / ml / year - is of questionable clinical relevance.
Men with a prior negative biopsy have a lower risk for prostate cancer at subsequent biopsies, with high grade disease particularly rare. We found little evidence to support the use of PSA velocity to aid decisions about repeat biopsy for prostate cancer.
We previously reported that a single prostate-specific antigen (PSA) measured at age 44–50 was highly predictive of subsequent prostate cancer diagnosis in an unscreened population. Here we report an additional seven years of follow-up. This provides a replication on an independent data set, and allows estimates of the association between early PSA and subsequent advanced cancer (clinical stage ≥T3 or metastases at diagnosis).
Blood was collected from 21,277 men in a Swedish city (74% participation rate) during 1974–1986 at age 33–50. Through 2006, prostate cancer was diagnosed in 1408 participants; we measured PSA in archived plasma for 1312 (93%) of these cases and for 3728 controls.
At a median follow-up of 23 years, baseline PSA was strongly associated with subsequent prostate cancer (area-under-the-curve 0.72; 95% CI 0.70, 0.74; for advanced cancer 0.75; 95% CI 0.72, 0.78). Associations between PSA and prostate cancer were virtually identical for the initial and replication data sets with 81% (95% CI 77%, 86%) of advanced cases found in men with PSA above the median (0.63 ng/ml at age 44 – 50).
A single PSA at or before age 50 predicts advanced prostate cancer diagnosed up to 30 years later. Use of early PSA to stratify risk would allow a large group of men to be screened less often but increase frequency of testing on a more limited number of high-risk men. This is likely to improve the ratio of benefits to harms for screening.
prostate cancer; prostate-specific antigen; human kallikrein 2; risk factors; case-control study
Oncologic outcomes in men with radiation-recurrent prostate cancer (PCa) treated with salvage radical prostatectomy (SRP) are poorly defined.
To identify predictors of biochemical recurrence (BCR), metastasis, and death following SRP to help select patients who may benefit from SRP.
Design, setting, and participants
This is a retrospective, international, multi-institutional cohort analysis. There was a median follow-up of 4.4 yr following SRP performed on 404 men with radiation-recurrent PCa from 1985 to 2009 in tertiary centers.
BCR after SRP was defined as a serum prostate-specific antigen (PSA) ≥0.1 or ≥0.2 ng/ml (depending on the institution). Secondary end points included progression to metastasis and cancer-specific death.
Results and limitations
Median age at SRP was 65 yr of age, and median pre-SRP PSA was 4.5 ng/ml. Following SRP, 195 patients experienced BCR, 64 developed metastases, and 40 died from PCa. At 10 yr after SRP, BCR-free survival, metastasis-free survival, and cancer-specific survival (CSS) probabilities were 37% (95% confidence interval [CI], 31–43), 77% (95% CI, 71–82), and 83% (95% CI, 76–88), respectively. On preoperative multivariable analysis, pre-SRP PSA and Gleason score at postradiation prostate biopsy predicted BCR (p = 0.022; global p < 0.001) and metastasis (p = 0.022; global p < 0.001). On postoperative multivariable analysis, pre-SRP PSA and pathologic Gleason score at SRP predicted BCR (p = 0.014; global p < 0.001) and metastasis (p < 0.001; global p < 0.001). Lymph node involvement (LNI) also predicted metastasis (p = 0.017). The main limitations of this study are its retrospective design and the follow-up period.
In a select group of patients who underwent SRP for radiation-recurrent PCa, freedom from clinical metastasis was observed in >75% of patients 10 yr after surgery. Patients with lower pre-SRP PSA levels and lower postradiation prostate biopsy Gleason score have the highest probability of cure from SRP.
Prostate cancer; Radiation therapy; Salvage therapy
Accurate preoperative and postoperative risk assessment has been critical for counseling patients regarding radical prostatectomy for clinically localized prostate cancer. In addition to other treatment modalities, neoadjuvant or adjuvant therapies have been considered. The growing literature suggested that the experience of the surgeon may affect the risk of prostate cancer recurrence. The purpose of this study was to develop and internally validate nomograms to predict the probability of recurrence, both preoperatively and postoperatively, with adjustment for standard parameters plus surgeon experience.
The study cohort included 7724 eligible prostate cancer patients treated with radical prostatectomy by 1 of 72 surgeons. For each patient, surgeon experience was coded as the total number of cases conducted by the surgeon before the patient’s operation. Multivariable Cox proportional hazards regression models were developed to predict recurrence. Discrimination and calibration of the models was assessed following bootstrapping methods, and the models were presented as nomograms.
In this combined series, the 10-year probability of recurrence was 23.9%. The nomograms were quite discriminating (preoperative concordance index, 0.767; postoperative concordance index, 0.812). Calibration appeared to be very good for each. Surgeon experience seemed to have a quite modest effect, especially postoperatively.
Nomograms have been developed that consider the surgeon’s experience as a predictor. The tools appeared to predict reasonably well but were somewhat little improved with the addition of surgeon experience as a predictor variable.
prostate cancer; surgeon experience; recurrence; predictive value; nomogram
Prostate-specific antigen (PSA) dynamics have been proposed to predict outcome in men with prostate cancer. We assessed the value of PSA velocity (PSAV) and doubling time (PSADT) for predicting prostate-cancer–specific mortality (PCSM) in men with clinically localized prostate cancer undergoing conservative management or early hormonal therapy. From 1990 to 1996, 2333 patients were identified, of whom 594 had two or more PSA values before diagnosis. We examined 12 definitions for PSADT and 10 for PSAV. Because each definition required PSA measurements at particular intervals, the number of patients eligible for each definition varied from 40 to 594 and number of events from 10 to 119. Four PSAV definitions, but no PSADT, were significantly associated with PCSM after adjustment for PSA in multivariable Cox proportional hazards regression. All 4 could be calculated only for a proportion of events, and the enhancements in predictive accuracy associated with PSAV had very wide confidence intervals. There was no clear benefit of PSAV in men with low PSA and Gleason grade 6 or less. Although evidence that certain PSAV definitions help predict PCSM in the cohort exist, the value of incorporating PSAV in predictive models to assist in determining eligibility for conservative management is, at best, uncertain.
prostate-specific antigen; prostate-specific antigen velocity; prostate-specific antigen doubling time; watchful waiting; prediction
We sought to assess the impact of prostate size on operative difficulty as measured by estimated blood loss (EBL), operating room (OR) time and positive surgical margins (SM) and secondarily to assess the impact on biochemical recurrence (BCR) and the functional outcomes of potency and continence at one year following radical prostatectomy (RP) as well as postoperative bladder neck contracture (BNC).
Materials and Methods
During 1998–2007, 3067 men underwent RP by one of 5 dedicated prostate surgeons with no neoadjuvant or adjuvant therapy. Pathologic specimen weight was used as a measure of prostate size. Cox proportional hazards and logistic regression analysis was used to study the association between specimen weight and biochemical recurrence (BCR) and SM status, respectively, controlling for adverse pathologic features. Continence and potency were analyzed controlling for age, nerve-sparing status, and surgical approach.
With increasing prostate size, there was increased EBL (p=0.013) and OR time (p=0.004) and a decrease in positive SM (84/632 (14%) for ≤40g, 99/862 (12%) for 41–50g, 78/842 (10%) for 51–65g, 68/731 (10%) for >65g (p<0.001)). BCR was observed in 186 of 2882 patients followed postoperatively and was not significantly associated with specimen weight (p=0.3). Complete continence was observed in 1165/1422 (82%) and potency in 425/827 (51%) at one year. Specimen weight was not significantly associated with potency (p=0.8), continence (p=0.08) or BNC (p=0.22).
Prostate size does not appear to affect biochemical recurrence or one-year functional results. However, EBL and OR time increased with larger prostate size and positive SM are more often observed in smaller glands.
organ volume; outcome assessment (health care); penile erection; prostatectomy; urinary incontinence
It has been demonstrated that complications and functional outcomes after prostate surgery vary between different surgeons to a greater extent than might be accounted for by chance. This type of excessive variation is known as “heterogeneity.” In this study, we explored whether there is also heterogeneity among high-volume surgeons with respect to cancer control after surgery.
Patients and Methods
The study cohort consisted of 7,725 patients with clinically localized prostate cancer treated by open radical prostatectomy at four major US academic medical centers 1987 – 2003 by one of 54 surgeons. We defined biochemical recurrence by a serum PSA level ≥ 0.4 ng/mL followed by a subsequent higher PSA level. Multivariable random effects models were used to evaluate the heterogeneity in prostate cancer recurrence between surgeons, after adjustment for case-mix (PSA, pathological stage and grade), year of surgery and surgeon experience.
We found statistically significant heterogeneity in prostate cancer recurrence rates (p=0.002) independent of surgeon experience. Seven experienced surgeons in our series had adjusted five-year prostate cancer recurrence rates less than 10%, while another five experienced surgeons had rates that exceed 25%. Significant heterogeneity remained in sensitivity analyses adjusting for possible differences in follow-up, patient selection and stage migration.
A patient's risk of recurrence may differ depending on which of two surgeons he sees, even if they have similar levels of experience. Surgical randomized trials are imperative to determine and characterize the roots of these variations
prostatic neoplasms; surgery; prostatectomy outcomes; recurrence. Surgeon; Experience; Volume. Variability; Heterogeneity; Differences
Prediction model; validation; nomogram; discrimination; calibration; decision curve
The relationship between prostate specific antigen (PSA) level and prostate cancer risk remains subject to fundamental disagreements. We hypothesize that the risk of prostate cancer on biopsy for a given PSA level is affected by identifiable characteristics of the cohort under study.
We used data from 5 European and 3 US cohorts of men undergoing biopsy for prostate cancer; six were population-based studies and two were clinical cohorts. The association between PSA and prostate cancer was calculated separately for each cohort using locally-weighted scatterplot smoothing.
The final data set included 25,772 biopsies and 8,503 cancers. There were gross disparities between cohorts with respect to both the prostate cancer risk at a given PSA level and the shape of the risk curve. These disparities were associated with identifiable differences between cohorts: for a given PSA level, a greater number of biopsy cores increased risk of cancer (odds ratio for >6 vs. 6 core biopsy 1.35; 95% C.I. 1.18, 1.54; p<0.0005); recent screening led to a smaller increase in risk per unit change in PSA (p=0.001 for interaction term) and US cohorts had higher risk than the European cohorts (2.14; 95% C.I. 1.99, 2.30; p<0.0005).
Our results suggest that the relationship between PSA and risk of a positive prostate biopsy varies, both in terms of the probability of prostate cancer at a given PSA value and the shape of the risk curve. This poses challenges to the use of PSA-driven algorithms to determine whether biopsy is indicated.
prostate cancer; PSA; prediction; multicenter studies; screening
We have developed a statistical prediction model for prostate cancer based on four kallikrein markers in blood: total, free, and intact prostate specific antigen (PSA) and kallikrein-related peptidase 2 (hK2). Although this model accurately predicts the result of biopsy in unscreened men, its properties for men with a history of PSA screening have not been fully characterized.
1501 previously screened men with elevated PSA underwent initial biopsy during rounds 2 and 3 of the European Randomized Study of Prostate Cancer Screening, Rotterdam, with 388 cancers diagnosed. Biomarker levels were measured in serum samples taken before biopsy. The prediction model developed on the unscreened cohort was then applied and predictions compared to biopsy outcome.
The previously developed four-kallikrein prediction model had much higher predictive accuracy than PSA and age alone (area-under-the-curve of 0.711 vs. 0.585 and 0.713 vs. 0.557 with and without digital rectal exam, respectively; both p<0.001). Similar statistically significant enhancements were seen for high-grade cancer. Applying the model with a cut-off of 20% cancer risk as the criterion for biopsy would reduce the biopsy rate by 362 for every 1000 men with elevated PSA. Although diagnosis would be delayed for 47 cancers, these would be predominately low stage and low grade (83% Gleason 6 T1c).
A panel of four kallikreins can help predict the result of initial biopsy in previously screened men with elevated PSA. Use of a statistical model based on the panel would substantially decrease rates of unnecessary biopsy.
prostate cancer; biomarkers; predictive value of tests; prostate-specific antigen; cancer screening
Risk models to predict prostate cancer on biopsy, whether they include only prostate-specific antigen (PSA) or other markers, are intended for use in all men of screening age. Yet the association between PSA and cancer likely depends on a man’s recent screening history.
To examine the effect of prior screening on prostate cancer risk prediction using a previously reported four-kallikrein panel: total, free, and intact PSA, and kallikrein-related peptidase 2 (hK2). The study cohort comprised 1241 men in Gothenburg, Sweden, undergoing biopsy for elevated PSA during their second or later visit for the European Randomized study of Screening for Prostate Cancer. We calculated the predictive accuracy of a four-kallikrein panel.
Total PSA was not predictive of prostate cancer. A previously published four-kallikrein model increased predictive accuracy compared to total PSA and age alone (area-under-the-curve [AUC] 0.66 vs. 0.51; p<0.001), but was poorly calibrated and missed many cancers. A model developed with recently screened men gave important improvements in discrimination (AUC 0.67 vs. 0.56; p<0.001). Use of this model would reduce the number of biopsies by 413 per 1000 men with elevated PSA, miss 60 of 216 low-grade (Gleason ≤6) cancers, but miss only 1 of 43 high-grade cancers.
Prior participation in PSA-screening dramatically changes the performance of statistical models predicting biopsy outcome. A four-kallikrein panel can predict prostate cancer in men with a recent screening history, providing independent replication that multiple kallikrein-forms contribute important diagnostic value in men with elevated PSA.
prostate cancer; screening; prostate specific antigen; kallikreins; molecular markers
Polymorphisms associated with prostate cancer include those in three genes encoding major secretory products of the prostate: KLK2 (encoding kallikrein-related peptidase 2; hK2), KLK3 (encoding prostate-specific antigen; PSA), and MSMB (encoding beta-microseminoprotein). PSA and hK2, members of the kallikrein family, are elevated in serum of men with prostate cancer. In a comprehensive analysis which included sequencing of all coding, flanking, and 2kb of putative promoter regions of all 15 kallikrein (KLK) genes spanning ≈280 Kb on chromosome 19q, we identified novel SNPs and genotyped 104 SNPs in 1419 cancer cases and 736 controls in CAPS1, with independent replication in 1267 cases and 901 controls in CAPS2. This verified prior associations of SNPs in KLK2 and in MSMB (but not in KLK3) with prostate cancer. Twelve SNPs in KLK2 and KLK3 were associated with levels of PSA forms or hK2 in plasma of control subjects. Based on our comprehensive approach, this is likely to represent all common KLK variants associated with these phenotypes. A T allele at rs198977 in KLK2 associated with increased cancer risk and a striking decrease of hK2 levels in blood. We also found a strong interaction between rs198977 genotype and hK2 levels in blood in predicting cancer risk. Based on this strong association, we developed a model for predicting prostate cancer risk from standard biomarkers, rs198977 genotype, and rs198977 x hK2 interaction; this model had greater accuracy than did biomarkers alone (AUC 0.874 vs 0.866), providing proof in principle to clinical application for our findings.
prostate cancer; prostate-specific antigen; human kallikrein-related peptidase 2; genetic variation; case-control study
Lead time, the estimated time by which screening advances the date of diagnosis, is used to calculate the risk of overdiagnosis. We sought to describe empirically the distribution of lead times between an elevated PSA and subsequent prostate cancer diagnosis.
We linked the Swedish cancer registry to two independent cohorts: 60-year olds sampled in 1981–1982 and 51–56-year olds sampled in 1982 – 1985. We used univariate kernel density estimation to characterize the lead time distribution. Linear regression was used to model the lead time as a function of baseline PSA and logistic regression was used to test for an association between lead time and either stage or grade at diagnosis.
132 of 1,167 older men were diagnosed with prostate cancer, of which 57 had PSA≥3ng/ml at baseline; 495 of 4,260 younger men were diagnosed with prostate cancer of which 116 had PSA≥3ng/ml at baseline. The median lead time was slightly longer in the younger men (12.8 versus 11.8 years). In both cohorts, wide variation in lead times followed an approximately normal distribution. Longer lead times were significantly associated with a lower risk of high-grade disease in older and younger men (OR: 0.82; p=0.023 and 0.77; p<0.001).
Our findings suggest that early changes in the natural history of the disease are associated with high-grade cancer at diagnosis.
The distinct differences between the observed distribution of lead times and those used in modeling studies illustrates the need to model overdiagnosis rates using empirical data.
Prostate cancer; lead time; overdiagnosis
We assessed the effect of radical prostatectomy (RP) and external beam radiotherapy (EBRT) on distant metastases (DM) rates in patients with localized prostate cancer treated with RP or EBRT at a single specialized cancer center.
Patients and Methods
Patients with clinical stages T1c-T3b prostate cancer were treated with intensity-modulated EBRT (≥ 81 Gy) or RP. Both cohorts included patients treated with salvage radiotherapy or androgen-deprivation therapy for biochemical failure. Salvage therapy for patients with RP was delivered a median of 13 months after biochemical failure compared with 69 months for EBRT patients. DM was compared controlling for patient age, clinical stage, serum prostate-specific antigen level, biopsy Gleason score, and year of treatment.
The 8-year probability of freedom from metastatic progression was 97% for RP patients and 93% for EBRT patients. After adjustment for case mix, surgery was associated with a reduced risk of metastasis (hazard ratio, 0.35; 95% CI, 0.19 to 0.65; P < .001). Results were similar for prostate cancer–specific mortality (hazard ratio, 0.32; 95% CI, 0.13 to 0.80; P = .015). Rates of metastatic progression were similar for favorable-risk disease (1.9% difference in 8-year metastasis-free survival), somewhat reduced for intermediate-risk disease (3.3%), and more substantially reduced in unfavorable-risk disease (7.8% in 8-year metastatic progression).
Metastatic progression is infrequent in men with low-risk prostate cancer treated with either RP or EBRT. RP patients with higher-risk disease treated had a lower risk of metastatic progression and prostate cancer–specific death than EBRT patients. These results may be confounded by differences in the use and timing of salvage therapy.
Cancer prediction models are becoming ubiquitous, yet we generally have no idea whether they do more good than harm. This is because current statistical methods for evaluating prediction models are uninformative as to their clinical value. Prediction models are typically evaluated in terms of discrimination or calibration. However, it is generally unclear how high discrimination needs to be before it is considered “high enough”; similarly, there are no rationale guidelines as to the degree of miscalibration that would discount clinical use of a model. Classification tables do present the results of models in more clinically relevant terms, but it is not always clear which of two models is preferable on the basis of a particular classification table, or even whether either model should be used at all. Recent years have seen the development of straightforward decision analytic techniques that evaluate prediction models in terms of their consequences. This depends on the simple approach of weighting true and false positives differently, to reflect that, for example, delaying the diagnosis of a cancer is more harmful than an unnecessary biopsy. Such decision analytic techniques hold the promise of determining whether clinical implementation of prediction models would do more good than harm.
We have observed that the area under the receiver operating characteristic curve (AUC) is increasingly being used to evaluate whether a novel predictor should be incorporated in a multivariable model to predict risk of disease. Frequently, investigators will approach the issue in two distinct stages: first, by testing whether the new predictor variable is significant in a multivariable regression model; second, by testing differences between the AUC of models with and without the predictor using the same data from which the predictive models were derived. These two steps often lead to discordant conclusions.
We conducted a simulation study in which two predictors, X and X*, were generated as standard normal variables with varying levels of predictive strength, represented by means that differed depending on the binary outcome Y. The data sets were analyzed using logistic regression, and likelihood ratio and Wald tests for the incremental contribution of X* were performed. The patient-specific predictors for each of the models were then used as data for a test comparing the two AUCs. Under the null, the size of the likelihood ratio and Wald tests were close to nominal, but the area test was extremely conservative, with test sizes less than 0.006 for all configurations studied. Where X* was associated with outcome, the area test had much lower power than the likelihood ratio and Wald tests.
Evaluation of the statistical significance of a new predictor when there are existing clinical predictors is most appropriately accomplished in the context of a regression model. Although comparison of AUCs is a conceptually equivalent approach to the likelihood ratio and Wald test, it has vastly inferior statistical properties. Use of both approaches will frequently lead to inconsistent conclusions. Nonetheless, comparison of receiver operating characteristic curves remains a useful descriptive tool for initial evaluation of whether a new predictor might be of clinical relevance.
Multivariable prediction models have been shown to predict cancer outcomes more accurately than cancer stage. The effects on clinical management are unclear. We aimed to determine whether a published multivariable prediction model for bladder cancer (“bladder nomogram”) improves medical decision making, using referral for adjuvant chemotherapy as a model.
We analyzed data from an international cohort study of 4462 patients undergoing cystectomy without chemotherapy 1969 – 2004. The number of patients eligible for chemotherapy was determined using pathologic stage criteria (lymph node positive or stage pT3 or pT4), and for three cut-offs on the bladder nomogram (10%, 25% and 70% risk of recurrence with surgery alone). The number of recurrences was calculated by applying a relative risk reduction to eligible patients' baseline risk. Clinical net benefit was then calculated by combining recurrences and treatments, weighting the latter by a factor related to drug tolerability.
A nomogram cut-off outperformed pathologic stage for chemotherapy for every scenario of drug effectiveness and tolerability. For a drug with a relative risk of 0.80, where clinicians would treat no more than 20 patients to prevent one recurrence, use of the nomogram was equivalent to a strategy that resulted in 60 fewer chemotherapy treatments per 1000 patients without any increase in recurrence rates.
Referring cystectomy patients to adjuvant chemotherapy on the basis of a multivariable model is likely to lead to better patient outcomes than the use of pathological stage. Further research is warranted to evaluate the clinical effects of multivariable prediction models.
ladder cancer; adjuvant chemotherapy; prognosis; decision support; outcomes
It has been suggested that changes in prostate-specific antigen (PSA) over time (ie, PSA velocity [PSAV]) aid prostate cancer detection. Some guidelines do incorporate PSAV cut points as an indication for biopsy.
To evaluate whether PSAV enhances prediction of biopsy outcome in a large, representative, population-based cohort.
Design, setting, and participants
There were 2742 screening-arm participants with PSA <3 ng/ml at initial screening in the European Randomized Study of Screening for Prostate Cancer in Rotterdam, Netherlands, or Göteborg, Sweden, and who were subsequently biopsied during rounds 2[en]6 due to elevated PSA.
Total, free, and intact PSA and human kallikrein 2 were measured for 1[en]6 screening rounds at intervals of 2 or 4 yr. We created logistic regression models to predict prostate cancer based on age and PSA, with or without free-to-total PSA ratio (%fPSA). PSAV was added to each model and any enhancement in predictive accuracy assessed by area under the curve (AUC).
Results and limitations
PSAV led to small enhancements in predictive accuracy (AUC of 0.569 vs 0.531; 0.626 vs 0.609 if %fPSA was included), although not for high-grade disease. The enhancement depended on modeling a nonlinear relationship between PSAV and cancer. There was no benefit if we excluded men with higher velocities, which were associated with lower risk. These results apply to men in a screening program with elevated PSA; men with prior negative biopsy were not evaluated in this study.
In men with PSA of about ≥3 ng/ml, we found little justification for formal calculation of PSAV or for use of PSAV cut points to determine biopsy. Informal assessment of PSAV will likely aid clinical judgment, such as a sudden rise in PSA suggesting prostatitis, which could be further evaluated before biopsy.
cancer detection; predictive models; prostate biopsy; prostate cancer; prostate-specific antigen; PSA velocity