Diagnostic Accuracy of Raman Spectroscopy for Prostate Cancer

A Systematic Review and Meta-Analysis

Jae Joon Park; Do Kyung Kim; Soomin Lee; Yoonseo Choi; Yon Hee Kim; Joon-Ho Lee; Ki Hyun Kim; Jae Heon Kim

Disclosures

Transl Androl Urol. 2021;10(2):574-583. 

In This Article

Abstract and Introduction

Abstract

Background: Although various studies have been conducted to demonstrate the possibility of Raman spectroscopy (RS) as a diagnostic tool for prostate cancer (PC), it is difficult to use it in the real clinical area because of imitations in various research processes. Therefore, we did a systematic review and meta-analysis about the accuracy in diagnostic use of RS for PC.

Methods: A literature search was done using PubMed, Embase, and Cochrane library databases in March 2019 to analyze the accuracy of RS for diagnosis of PC. The accuracy of RS for diagnosis of PC was evaluated by means of pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC).

Results: Five studies were included for qualitative analysis by screening the remaining articles according to the inclusion and exclusion criteria by means of a systematic review. The pooled sensitivity and specificity of RS were 0.89 (95% CI: 0.87–0.91) and 0.91 (95% CI: 0.89–0.93), respectively. The overall PLR and NLR were 9.12 (95% CI: 4.15–20.08) and 0.14 (95% CI: 0.07–0.29), respectively. The DOR of RS demonstrated high accuracy (73.32; 95% CI: 18.43–291.73). The area under the curves (AUCs) of SROC curves was 0.93.

Conclusions: RS is an optical diagnostic method with high potential for diagnosis and grading of PC and has advantages of real-time and convenient use. In order to consider real-time use of RS in an actual clinical setting, more studies for standardization and generalization of RS performance and analytical method must be conducted.

Introduction

Prostate cancer (PC), of which 70% occur in developed countries is the most common male cancer with 174,650 newly diagnosed cases and ranks second in cancer related death in 2019 in the United states.[1,2] Thus, it causes a considerable public-health burden, but there is a strong potential to reduce PC specific mortality rates via screening.[3]

In the past 20 years, the use of serum prostate-specific antigen (PSA) levels as a diagnostic tool for PC has increased detection at an early stage by increasing the number of men suggested for prostate biopsy.[4–6] However, the level of PSA in serum is not an ideal cancer marker, because elevated PSA levels in many other conditions can cause overdiagnosis.[4,5] Meanwhile, the gold standard for detection of PC is pathological examination using ultrasound-guided transrectal prostate biopsy.[7] However, this procedure is invasive, accompanied by significant risk of complications, and costly.[6] Researchers have been pursuing minimally invasive diagnostic methods that can provide diagnostic information at the molecular level and be reliable because of their high specificity and sensitivity.[8]

In this respect, Raman spectroscopy (RS) has recently received attention as an attractive alternative for cancer detection.[9] RS, which analyzes inelastic scattering of a photon having unique energy levels depending on every molecule type, has been used as an important diagnostic tool in many research disciplines.[10,11] With development of spectroscopic instruments and technology, RS has advanced to evaluate cancer and precancerous lesions in multiple organs.[12,13] RS has also been applied in the area of PC, and studies on it have revealed variations from adenocarcinoma to benign prostatic hyperplasia (BPH) at the molecular level.[14,15] Crow et al. confirmed that RS can accurately discriminate BPH and three different grades of PC through a diagnostic algorithm using principal components analysis (PCA) method.[16] Lopes et al. helped establish a concise spectral model to predict the concentration of spectral features to identify normal, BPH, and prostate carcinoma tissues in vitro.[8]

The objective of our study was to work up a spectral model based on dispersive RS to differentiate the prostate biochemical differences between benign lesions and malignancy.[14] Despite these efforts, it is difficult to define RS as a critical diagnostic method, because the number of samples for studies was small, and the sampling method, diagnostic algorithms, analysis tools, and RS settings in previous studies were not unified. Therefore, to verify the accuracy of RS as a diagnostic tool for PC by using current evidence, we did both a qualitative and quantitative analysis, as was essential.

We present the following article in accordance with the PRISMA reporting checklist (available at http://dx.doi.org/10.21037/tau-20-924).

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