Abstract
BACKGROUND
Magnetic resonance imaging localises cancer in the prostate, allowing for a targeted biopsy with or without transrectal ultrasound-guided systematic biopsy. Targeted biopsy methods include cognitive fusion, where prostate lesions suspicious on magnetic resonance imaging are targeted visually during live ultrasound, and software fusion, where computer software overlays the magnetic resonance imaging image onto the ultrasound in real time. The effectiveness and cost-effectiveness of software fusion technologies compared with cognitive fusion biopsy are uncertain.
OBJECTIVES
To assess the clinical and cost-effectiveness of software fusion biopsy technologies in people with suspected localised and locally advanced prostate cancer. A systematic review was conducted to evaluate the diagnostic accuracy, clinical efficacy and practical implementation of nine software fusion devices compared to cognitive fusion biopsies, and with each other, in people with suspected prostate cancer. Comprehensive searches including MEDLINE, and Embase were conducted up to August 2022 to identify studies which compared software fusion and cognitive fusion biopsies in people with suspected prostate cancer. Risk of bias was assessed with quality assessment of diagnostic accuracy studies-comparative tool. A network meta-analysis comparing software and cognitive fusion with or without concomitant systematic biopsy, and systematic biopsy alone was conducted. Additional outcomes, including safety and usability, were synthesised narratively. A de novo decision model was developed to estimate the cost-effectiveness of targeted software fusion biopsy relative to cognitive fusion biopsy with or without concomitant systematic biopsy for prostate cancer identification in biopsy-naive people. Scenario analyses were undertaken to explore the robustness of the results to variation in the model data sources and alternative assumptions.
RESULTS
Twenty-three studies (3773 patients with software fusion, 2154 cognitive fusion) were included, of which 13 informed the main meta-analyses. Evidence was available for seven of the nine fusion devices specified in the protocol and at high risk of bias. The meta-analyses show that patients undergoing software fusion biopsy may have: (1) a lower probability of being classified as not having cancer, (2) similar probability of being classified as having non-clinically significant cancer (International Society of Urological Pathology grade 1) and (3) higher probability of being classified at higher International Society of Urological Pathology grades, particularly International Society of Urological Pathology 2. Similar results were obtained when comparing between same biopsy methods where both were combined with systematic biopsy. Evidence was insufficient to conclude whether any individual devices were superior to cognitive fusion, or whether some software fusion technologies were superior to others. Uncertainty in the relative diagnostic accuracy of software fusion versus cognitive fusion reduce the strength of any statements on its cost-effectiveness. The economic analysis suggests incremental cost-effectiveness ratios for software fusion biopsy versus cognitive fusion are within the bounds of cost-effectiveness (£1826 and £5623 per additional quality-adjusted life-year with or with concomitant systematic biopsy, respectively), but this finding needs cautious interpretation.
LIMITATIONS
There was insufficient evidence to explore the impact of effect modifiers.
CONCLUSIONS
Software fusion biopsies may be associated with increased cancer detection in relation to cognitive fusion biopsies, but the evidence is at high risk of bias. Sufficiently powered, high-quality studies are required. Cost-effectiveness results should be interpreted with caution given the limitations of the diagnostic accuracy evidence.
STUDY REGISTRATION
This trial is registered as PROSPERO CRD42022329259.
FUNDING
This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: 135477) and is published in full in Health Technology Assessment; Vol. 28, No. 61. See the NIHR Funding and Awards website for further information.
Plain language summary
Men with an magnetic resonance imaging scan that shows possible prostate cancer (PCa) are offered prostate biopsies, where samples of the prostate tissue are collected with a needle, to confirm the presence and severity of cancer. Different biopsy methods exist. In a cognitive fusion biopsy, clinicians will target abnormal looking parts of the prostate by looking at the magnetic resonance imaging scan alongside ‘live’ ultrasound images. During a software fusion (SF) biopsy, a computer software is used to overlay the magnetic resonance imaging scan onto the ultrasound image. This study evaluated whether SF is better at detecting cancer compared with cognitive fusion biopsy, and whether it represents value for money for the National Health Service. We did a comprehensive review of the literature. We combined and re-analysed the evidence, and assessed its quality. We investigated whether SF biopsies are sufficient value for money. Compared with cognitive fusion, patients receiving a SF biopsy may have: (1) a lower probability of having a ‘no cancer’ result, (2) similar probability of having a benign, non-clinically significant (CS) cancer result and (3) higher probability of detecting CS cancer. However, it is uncertain to what extent SF is more accurate than cognitive fusion, because of concerns about the quality of the evidence. We found no evidence that any SF devices were superior to others. Using additional, random biopsies alongside software or cognitive fusion would increase the detection of PCa. We also looked for evidence on the value for money of the SF biopsies to detect PCa and found no relevant studies. We weighed the costs and the benefits of SF biopsy compared to cognitive fusion to determine whether it could be a good use of National Health Service money. The poor quality of information makes the value of the technologies largely unknown.
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