Development and validation of risk score for predicting positive repeat prostate biopsy in patients with a previous negative biopsy in a UK population

The majority of the 35000 new diagnoses of prostate cancer annually in the UK [1] are made as a result of transrectal ultrasound-guided (TRUS) biopsies of the prostate performed to investigate an elevated serum PSA or abnormal digital rectal examination. Seventy-five percent of cancers identified are detected at the first biopsy [2]. The majority of men undergoing this procedure, however, will not have a cancer detected and doubt will remain both in their minds and in those of the clinician as to whether a further biopsy is required in the setting of a persistently abnormal or rising serum PSA. Prostate biopsy is not without morbidity [3] carrying a 1% risk of sepsis or severe haemorrhage, and 5% risk of urinary tract infection, and the need to reduce unnecessary repeat biopsies was further highlighted recently in the UK with the publication of NICE guidelines for prostate cancer [4]. This document estimated that 89000 prostate biopsies are performed annually in the UK. Twenty percent of cancers are detected at the second biopsy session [5], and a number of parameters have been promoted to reduce the frequency of benign repeat biopsy. Abnormal digital rectal examination (DRE) [6], PSA [5], PSA velocity > 0.75 ng/ml/yr [7], PSA density > 0.15 [5, 7] transition zone density > 0.25 [5, 8], and free-to-total PSA ratio [5, 7], as well as initial histological findings of high grade prostatic intraepithelial neoplasia (HGPIN) [6, 8] or suspicious histology [9] have all been used to identify those men at higher risk of positive repeat biopsy. These individual parameters when taken alone, have poor positive and negative predictive value [5]. Kattan has produced a number of predictive nomograms to aid decision making in prostate cancer [10], including one intended to enhance prediction of positive repeat biopsies, based on sextant prostate biopsy data [11]. It was suggested that the model could be improved through adding free-to-total PSA ratio and prostate volume to the calculation. The aim of this study was to use a similar approach for a United Kingdom population in order to produce a more accurate predictive tool to be used in the outpatient setting when faced with a patient who may be a candidate for a second TRUS and biopsy of the prostate.

All patients who underwent first repeat prostate biopsy sessions at two hospitals in the former West Anglia Cancer Network with a combined catchment population of more that 1.25 million were studied. Those who had an initial negative biopsy were analysed. Indications for repeat biopsy and the number of biopsy cores taken were similar in both hospitals according to local guidelines, with an extended core biopsy template (at least 10 cores including anterior horn of the peripheral zone). Prostate biopsies were performed using TRUS guidance with a 7.5 MHz probe (B&K), biopsy gun (Bard) and an 18 gauge biopsy needle with local anesthesia.

The clinical parameters recorded for each patient were age, serum PSA, PSA velocity in ng/ml/year (measured over 18 months), prostate volume, DRE findings, time interval between biopsy sessions, and history of HGPIN or suspicious histology. Data was collected from an anonymised database. Research was carried out in compliance with the Helsinki Declaration.

Clinicians use various triggers for proceeding to repeat prostate biopsies. Serum PSA, (which may be age-adjusted), age, DRE findings, free-to-total PSA ratio, transition zone PSA density, standard PSA density, PSA velocity and the finding of HGPIN on initial biopsy have all been used in this setting [1–5].

The predictive value of these individual factors is limited, however, and this has led to attempts to refine the prediction process and reduce the frequency of unnecessary repeat biopsies. Artificial neural networks and nomograms have been used to this end [11–14] but have not gained wide acceptance in clinical practice.

The detection rate of cancer on second and further biopsies is thought to be lower than the initial procedure. Kattan's group showed that the rate decreased from 19.5% in the second biopsy to 13.5% after 5 or more biopsy sessions [11]. This data and previous studies were, however, based on initial sextant biopsies. In our study, the rate of positive biopsies remained steady at 30%, and the distribution of cancer grade did not change suggesting that even in the era of extended core prostate biopsies initial benign biopsies do not preclude a diagnosis of significant cancer on subsequent investigation.

Identifying those men who require repeat biopsy whilst avoiding unnecessary biopsies is not straightforward. Djavan found that free-to-total PSA ratio and transition zone PSA density were useful predictive factors with AUCs of 74% and 69% [13]. Keetch et al have shown PSA density and PSA velocity to be better predictors [15] suggesting that using more than one variable in determining further biopsy is beneficial, but that the ideal combination is unknown.

The Kattan nomogram included a selection of risk factors that can predict the presence of cancer, and this model was validated in a second repeat biopsy population with an AUC of 71% [14].

Gallo [16] and Akhavan [17] have recently questioned the predictive value of HGPIN in repeat biopsy, and our model supports this view, as adding this variable to the regression model did not increase the accuracy of prediction. However, other authors have suggested that the finding of multifocal HGPIN should be viewed with more suspicion [18].

Kattan showed that incorporating multiple variables can vastly improve on the predicted probability of having prostate cancer [11]. We have adapted this approach to the extended core repeat prostate biopsy population in a UK setting, and improved the accuracy through adding the additional variables of prostate volume and free-to-total PSA ratio.

This nomogram (AUC 0.82, 95%CI 0.71 – 0.93) performed favourably when compared with Kattan's which had an AUC of 0.75. This may be a result of the incorporation of additional variables to the model. This predictive tool is based on men who present either with symptoms, or as a result of opportunistic screening. Whether this predictive tool is applicable to a setting where PSA testing for screening purposes is more widely available needs to be investigated. This model has been internally validated, but re-validation on external populations should be the next step.

The decision to repeat a prostate biopsy must be made after informed discussion between clinician and patient, following a multi-disciplinary team meeting case discussion. A nomogram can aid decision making in this setting. The probability of cancer on repeat biopsy generated by this predictive tool reflects the probability that a man with the same clinical parameters investigated in the same manner as those included in this retrospective analysis would have a positive repeat biopsy. This figure will be interpreted by the patient according to his perception of risk to inform his choice. A precise cut-off to trigger a repeat biopsy is difficult to produce, and will vary according to an individual patient's and urologist's perception of risk, however, using a calculated risk score threshold for re-biopsy of 0.45 (sensitivity 70%, specificity 83%) would reduce the number of unnecessary biopsies in this study (absolute reduction 69%) while identifying 65% of the cancers. Alternatively a more conservative approach using a risk-score threshold for biopsy of > 0.2 would reduce the number of biopsies by 39% while identifying 90% of patients with cancer. As such this study has policy implications. Implementing such a threshold risk score to trigger repeat biopsy could reduce the number of repeat biopsies in the UK by up to 4100 per year, equating to a saving of €1.25 million, prevention of 40 life-threatening hospital admissions for urinary sepsis, and 200 fewer urinary tract infections.

Strengths of the study

The predictive tool was developed based on data from one population sample and was tested in an independent sample. Application of the risk scores to an independent sample with good and comparable performance supports the validity of the developed risk score model. A webtool has been developed which is accessible, easy to use, and is based on parameters readily available to the clinician during an outpatient consultation. This facilitates discussion of the risk estimates in real time with the patient and further management planned in an informed fashion (Figure 3).

We have developed a web-based predictive tool for a UK population which is comparable to previous published predictive nomograms to aid decision-making in men with persistently abnormal PSA who are considering a repeat prostate biopsy. Using such risk score prediction model in clinical practice, could help in forming a strategy for reducing the number of unnecessary repeat biopsies.