A randomised trial comparing two protocols for transrectal prostate repeat biopsy: six lateral posterior plus six anterior cores versus a standard posterior 12-core biopsy

Accuracy of a new electronic nose for prostate cancer diagnosis in urine samples

Objective

To evaluate the accuracy of a new electronic nose to recognize prostate cancer in urine samples.

Methods

A blind, prospective study on consecutive patients was designed. Overall, 174 subjects were included in the study: 88 (50.6%) in prostate cancer group, and 86 (49.4%) in control group. Electronic nose performance for prostate cancer was assessed using sensitivity and specificity. The diagnostic accuracy of electronic nose was reported as area under the receiver operating characteristic curve.

Results

The electronic nose in the study population reached a sensitivity 85.2% (95% confidence interval 76.1–91.9; 13 false negatives out of 88), a specificity 79.1% (95% confidence interval 69.0–87.1; 18 false positives out of 86). The accuracy of the electronic nose represented as area under the receiver operating characteristic curve 0.821 (95% confidence interval 0.764–0.879).

Conclusions

The diagnostic accuracy of electronic nose for recognizing prostate cancer in urine samples is high, promising and susceptible to supplemental improvement. Additionally, further studies will be necessary to design a clinical trial to validate electronic nose application in diagnostic prostate cancer nomograms.

Drift compensation on electronic nose data for non-invasive diagnosis of prostate cancer by urine analysis

Diagnostic protocol for prostate cancer (KP) is affected by poor accuracy and high false-positive rate. The most promising innovative approach is based on urine analysis by electronic noses (ENs), highlighting a specific correlation between urine alteration and KP presence. Although EN could be exploited to develop non-invasive KP diagnostic tools, no study has already introduced EN into clinical practice, most probably because of drift issues that hinder EN scaling up from research objects to large-scale diagnostic devices. This study, proposing an EN for non-invasive KP detection, describes the data processing protocol applied to a urine headspace dataset acquired over 9 months, comprising 81 patients with KP and 41 controls, for compensating the drift. It proved effective in mitigating drift on 1-year-old sensors by restoring accuracy from 55% up to 80%, achieved by new sensors not subjected to drift. The model achieved, on double-blind validation, a balanced accuracy of 76.2% (CI_95% 51.9–92.3).

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Urine odor alteration due to prostate cancer can be detected by electronic noses

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Sensors drift hinders electronic nose scaling up to large-scale diagnostic devices

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OSC mitigates drift on 1-year-old sensors, restoring accuracy from 55% up to 80%