Ratios of Prostate-Specific Antigen to Albumin, C-reactive Protein, and Haemoglobin Concentration are Valuable Markers to Predict Patients with Either Prostate Cancer or Benign Prostate Hyperplasia

Ratios of Prostate-Specific Antigen to Albumin, C-reactive Protein, and Haemoglobin Concentration are Valuable Markers to Predict Patients with Either Prostate Cancer or Benign Prostate Hyperplasia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Ratios of Prostate-Specific Antigen to Albumin, C-reactive Protein, and Haemoglobin Concentration are Valuable Markers to Predict Patients with Either Prostate Cancer or Benign Prostate Hyperplasia Yaw Adjei Mensah-Bonsu, Kwaku Addai Arhin Appiah, Victor Dedjoe, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4326102/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Prostate Cancer (PCa) diagnosis using PSA alone leads to unnecessary biopsy due to the non-specificity of PSA for PCa. Changes in systemic inflammation variables with the development and progression of PCa cancer have been widely acknowledged. This study evaluated the potential utility of ratios involving changes in serum PSA with changes in systemic inflammatory components: serum albumin, C-reactive protein, and full blood count differentials, to differentially predict PCa biopsy in a cohort of pre-biopsy patients. Methods : We prospectively analyzed data from 110 patients who underwent prostate biopsy between September 2022 and September 2023. Age, PSA, full blood count, serum albumin (ALB), serum C-reactive protein (CRP) and biopsy pathology results of the patients were analyzed. Based on biopsy findings, patients were grouped as benign prostatic hyperplasia (BPH) and PCa. Results : Analyses of ratios involving PSA and the selected inflammatory markers led to wider discriminating values between PCa and BPH. The mean PSA-to-ALB, PSA-to-Hb and PSA-to-CRP ratios were significantly lower in the BPH group compared with the PCa group. AUROC curves analysis at cut-off points of PSA-ALB˃1, PSA-CRP˃250 and PSA-Hb˃2.5 resulted in specificity and positive predictive values for PSA-to-ALB ratio of 93% and 91% respectively, PSA-to-Hb ratio of 86% and 80% respectively and PSA-to-CRP ratio of 78% and 77% respectively. Unconditional regression analysis showed that PSA-to-CRP, PSA-to-Hb and PSA-to-ALB ratios were independent predictors of positive PCa biopsy. Conclusion : This preliminary study suggests that, the combination of PSA with changes in serum inflammatory variables in ratios improved the diagnostic accuracy more than the use of PSA alone. These ratios may assist in the differential prediction of PCa and BPH, especially where biopsy services are not readily available in Low- and Middle-Income countries. benign prostate hyperplasia biopsy differential diagnosis inflammation prostate cancer BACKGROUND Prostate Cancer (PCa) is a growing concern in Africa according to the International Agency for Research on Cancer (IARC) GLOBOCAN. In sub-Sahara Africa, PCa deaths are predicted to more than double from 47,000 in 2020 to 100,000 by 2040 [ 1 ]. This projected increase is partly due to the absence of screening, challenges with early diagnosis, and acute lack of experts and facilities for urological care among others [ 2 – 4 ]. Therefore the majority of sub-Saharan Africa (SSA) PCa cases are diagnosed with aggressive disease, often at late stages [ 5 , 6 ]. Digital rectal exam (DRE) is more widely used, however, this is not well-accepted by patients, as it is not very sensitive, and unable to detect potentially curable early-stage cancers. Due to these challenges associated with DRE, PCa is often not detected until the disease is at an advanced stage, when symptoms such as pain or urinary problems push patients to seek medical care [ 7 , 8 ]. The widespread introduction of serum prostate-specific antigen (PSA) test as a screening tool for PCa enhanced the early detection of PCa and reduced the associated mortality [ 9 , 10 ]. However, low specificity of PSA for PCa leads to unnecessary biopsies, over-diagnosis and overtreatment [ 11 ]. In view of the limitation of DRE and PSA test, guided biopsy detection remains the gold standard for diagnosing PCa [ 12 , 13 ]. However, this is often not possible because of the cost and limitations in urology (ultrasound-guided biopsies) and biopsy pathology services [ 13 ], particularly in rural areas where most of the SSA populations live [ 14 ]. Over the years, PSA-related testing parameters (for example, PSA density, free/total PSA ratio, PSA doubling time, and prostate health index test) have been explored to improve the accuracy of the PSA diagnosis of PCa. However, concerns about the specificity still remains [ 15 ]. Therefore, new biomarker(s) with higher specificity to differentially predict PCa from benign conditions to improve diagnosis and clinical decision-making when biopsy (BPx) option is not readily available is urgently needed. It has become increasingly clear that inflammation plays an important role in the development and progression of cancer. Cancer development and progression are dependent on a complex interaction of the tumour and the host inflammatory response [ 16 , 17 ]. It is therefore not surprising that changes in the levels of systemic inflammatory markers such as serum albumin and C-reactive protein do occur during the development and progression of a variety of primary operable tumours, including PCa [ 18 ]. Earlier studies have reported that low pre-operative levels of serum albumin predicts lymph node metastases and biochemical recurrence of prostate cancer in radical prostatectomy patients [ 19 , 20 ]. Elevated C-reactive protein levels predicts reduced survival and a poor response to chemotherapy in patients with advanced prostate cancer [ 21 ]. However, to our knowledge, no study has investigated changes in serum PSA dynamics with systemic inflammatory response variables to differentially predict diagnosis of prostate cancer or benign prostate hyperplasia. The goal of this prospective study was to evaluate the potential use of ratios of serum PSA to pre-treatment serum albumin, C-reactive protein and full blood count differentials to differentially predict diagnosis of prostate cancer or benign prostate hyperplasia in a cohort of pre-biopsy patients. METHODS Study Population Informed consent was sought from participants before involvement in the study. All patients suspected of prostate cancer or BPH who were scheduled for biopsy were eligible based on pre-diagnostic investigations using PSA, ultrasound imaging and digital rectal examinations. Patients with hepatopathy, coagulation-related diseases, inflammatory diseases, autoimmune diseases, cardiovascular and cerebrovascular diseases were excluded. Also, patients with symptomatic prostatitis or urinary tract infection or systemic inflammatory disease or any history of anti-inflammatory drug use within 2 weeks before biopsy (PBx) were excluded. Structured questionnaires were administered and participants were assisted to complete them. Blood processing After completing the questionnaire, 5ml venous blood samples were collected separately into EDTA tube, for full blood count determination and Gel-clot activator tube, for the chemistries. Samples collected into the Gel-clot activator tubes were processed to obtain the serum. Samples in the EDTA tube were run within 24 hours using a 3-part fully automated haematology analyzer. Biopsy Ultrasound-guided prostate biopsies were taken by attending urologists and samples obtained were sent for histopathological examination to determine the presence of tumour and grade (Gleason score) and those that were benign were also recorded. Serum Prostate Specific Antigen Estimation Total serum PSA was determined using PSA Enzyme Immunoassay test kits according to the manufacturer’s protocol. A microplate reader (iMark™, Bio-Rad Laboratories, USA) was used to read the optical density at 450 nm within 15 minutes of colour development. Systemic Inflammation Assessment (Laboratory assays) Full blood cell counts with differential counts were assessed using automated analyzer (Fluorescence flow cytometry, Sysmex 2100). C-reactive protein concentration was measured using a sensitive double antibody sandwich ELISA with rabbit anti-human C-reactive protein and peroxidase-conjugated rabbit anti-human C-reactive protein. The assay was linear from 0.1 to 5 mg/l and logarithmic thereafter. Serum albumin levels were estimated using Bromcresol Green method [ 22 ]. Serum PSA/ Albumin concentration (PSA-to-ALB) ratio, PSA/C-Reactive protein concentration (PSA-to-CRP) ratio, and PSA/Haemoglobin concentration (PSA-to-Hb) ratio were calculated to assess changes in PSA to changes in the measured systemic inflammatory markers. The institutional review board of the Kwame Nkrumah University of Science and Technology approved this study (CHRPE/AP/629/22). Data analysis Biopsy results, PSA, complete blood count (CBC), Serum biomarkers (C-reactive protein and albumin), PSA-to-CRP ratio, PSA-to-Hb ratio and PSA-to-ALB ratios were compared between PCa and BPH using t -test. Unconditional logistic regression was used to examine the significance of the association between the ratios (PSA-to-ALB ratio, PSA-to-CRP and PSA-to-Hb concentration) with biopsy outcomes (prostate cancer or BPH). Furthermore, univariate and multivariate logistic regression analyses were performed to determine predictors of either BPH or PCa diagnosis. The predictive accuracy of the multivariate model was assessed using receiver operating characteristic (ROC)-derived area under the curve (AUC) analysis. The statistical analysis was performed using Graph pad prism version 5.0.3 and Microsoft excel 2016. A two-tailed p < 0.05 was considered significant for all analyses. RESULTS A total of 110 patients who underwent transrectal ultrasound-guided PBx were grouped based on histological finding of the biopsy into BPH (n=35 patients) and PCa (n = 75). The mean age of BPH cohort was 70 years and 67 years for PCa. About half of the total participants had normal BMI: BPH (51.8%) and PCa (47.4%). The majority of the patients recruited for the study were hypertensive (75% of BPH, and 80% of PCa). The mean serum PSA of the PCa group (176.2 ± 53.44 ng/ml) was significantly higher than the BPH group (22.55 ± 4.08 ng/ml). Except for haemoglobin (Hb) concentration which was significantly lower in the PCa group compared with the BPH group, there were no significant differences in the full blood count differentials between the two groups (Tab. 1). Furthermore, the differences in the systemic negative acute inflammatory marker, Albumin (ALB) was significantly lower in the PCa compared with the BPH group. On the other hand, higher mean values of the positive acute inflammatory marker, C-reactive protein, was recorded in the PCa compared with BPH group indicating a differential response of these systemic inflammatory marker responses to BPH and PCa (Tab. 1). In light of the significant differences observed in serum ALB, Hb concentration and CRP between PCa and BPH groups, further analyses were carried out to investigate ratios involving PSA and the three biomarkers to obtain threshold values that differentiate significantly between PCa and BPH. Here we report on Ratios involving circulating negative and positive acute inflammatory proteins for prognostic threshold, such that the outcome is effectively stratified to differentiate between BPH and PCa. Below in table 2 are findings on the ratios with potential utility in predicting PCa and BPH. The mean PSA-to-ALB ratio was significantly lower in the BPH (0.53 ± 0.10) group compared with the PCa group (2.867 ± 0.60) at p ˂ 0.0001. Similarly, mean PSA-to-Hb ratio was significantly lower in the BPH group (1.75 ± 0.31) compared with the PCa group (11.41 ± 2.91) at p ˂ 0.0001. Finally, PSA-to-CRP values were significantly lower in the BPH group (181.0 ± 38.81) compared with the PCa group (435.7 ± 86.03) at p-value = 0.014. The Receiver Operating Characteristics (ROC) curve analyses were carried out to assess the ability of the ratios to differentially predict PCa or BPH based on sensitivity, specificity, positive predictive value and negative predictive values. Therefore, based on the Area Under the ROC (AUROC) curves analyses, the cut-off points of PSA-to-ALB, PSA-to-CRP and PSA-to-Hb ratios were 1.00, 250 and 2.5 respectively (Tab. 3a). Multivariate analysis showed that PSA-to-CRP (odds ratio (OR) = 2.01 (0.80 - 5.03), PSA-to-Hb (OR = 5.87 (2.27 - 15.16)) and PSA-to-ALB ratio (OR = 12.86 (3.62 - 45.71)) were independent predictors of PCa (Table 3b). The sensitivities, specificities, positive predictive values, and negative predictive values using PSA/CRP cut-off, PSA/Hb cut-off, and PSA/Alb cut-off are shown in Table 3b. Specificity and positive predictive value of PSA-to-ALB ratio was the highest (93% and 91% respectively), followed by PSA-to-Hb ratio (86 %, 80 % respectively) and the least was PSA-to-CRP (78 % and 77 % respectively) (Table 3b). Analysis of PSA-to-ALB ratio resulted in much significant disparity between PCa and BPH patients with specificity of 93% (81 - 98) and positive predictive value of 91% (77 - 98) at a cut-off of PSA/ALB ≥ 1.0 compared with either PSA alone with specificity of 55% (43 - 68) and PPV of 17% (7 - 34) or Albumin alone with specificity of 61% (49 - 72) and PPV of 17% (7 - 34) from our studies (Tab. 3b). Similarly, a ratio of PSA-to-Hb concentration resulted in much larger discriminating values of specificity 86% (74 - 94) and PPV of 80% (61 - 92) at a cut-off of 2.5 for PCa prediction compared with the individual variables which showed relatively less specificity and PPV (Tab. 3b). Furthermore, our assessment of PSA-to-CRP ratio revealed much significant discriminating values with higher specificity and PPV compared with the individual measured variables. Therefore, it can be concluded that PSA-to-ALB, PSA-to-Hb and PSA-to-CRP resulted in higher disparities between PCa and BPH such that they were effective in stratifying PCa from BPH in our cohort of patients. Table 1. Comparison of serum markers and Full blood count between BPH and PCa groups Table 1: Comparison of serum PSA, Full blood count and selected serum inflammatory markers between benign prostate hyperplasia (BPH) group and prostate cancer (PCa) group. Results are mean ± SD, * signifies p -value ≤ 0.05. Table 2. A comparison of ratios of serum PSA to selected systemic inflammatory markers between Benign prostate hyperplasia (BPH) and Prostate cancer (PCa). PSA/Blood Inflammation Marker Ratio BPH 95% CI PCa 95% CI P- value PSA/ALB 0.53 ± 0.10 0.33 – 0.73 2.867 ± 0.60 1.67 – 4.07 < 0.0001 PSA/CRP 181.0 ± 38.81 102.1 – 259.9 435.7 ± 86.03 264.3 – 607.1 0.0145 PSA/Hb 1.75 ± 0.31 1.13 – 2.42 11.41 ± 2.91 6.94 -16.93 < 0.0001 Table 2: A comparison of ratios of serum PSA to selected systemic inflammatory markers between Benign prostate hyperplasia (BPH) and Prostate cancer (PCa). PSA/CRP ratio, serum prostate-specific antigen to C-reactive protein ratio; PSA/ALB – serum prostate-specific antigen to serum Albumin ratio; PSA/Hb – serum prostate-specific antigen to Haemoglobin ratio. PCa (n= 75), BPH (n=35). Results are mean + SD, * signifies p -value ≤ 0.05. Table 3a. AUROC for variables and PSA-ratios predicting Prostate cancer Biopsy. Variable Area ( ± SEM) 95% CI P value PSA 0.67 (±0.05) 0.57 - 0.77 0.004 ALB 0.68 (±0.04) 0.58 - 0.78 0.003 CRP 0.69 (±0.05) 0.59 - 0.80 0.001 Hb 0.69 (±0.05) 0.59 - 0.80 0.001 Ratio Area ( ± SEM) 95% CI P value PSA/ALB 0.7667 (± 0.05) 0.68 - 0.86 < 0.0001 PSA/CRP 0.6453 (± 0.058) 0.53 - 0.76 0.014 PSA/Hb 0.7794 (± 0.04) 0.69 - 0.87 < 0.0001 Table 3a: Data on the Area Under the Receiver Operating characteristic curves (AUROC) for PSA, ALB, CRP and Hb compared with PSA/CRP, PSA/Hb and PSA/ALB ratios to predict PCa. PSA/Hb and PSA/ALB ratios resulted in higher AUROC than the individual variables. PSA - prostate-specific antigen, ALB - Albumin, CRP - C-reactive protein and Hb - haemoglobin concentration Table 3b. An AUROC analysis and unconditional logistic regression analyses on individual variable and their ratio with PSA to predict prostate cancer biopsy. Table 3b : AUROC analysis on individual variable and their ratio with PSA to predict prostate cancer biopsy in the study cohort. Unconditional logistic regression analyses assessing the association of individual variables and ratios with Prostate cancer. These studies involved PCa (n=75) cases and BPH (n=35) cases. The specificities, positive predictive values and other predictive values of the ratios showed higher predictive values compared with that of the individual variables. Results are shown as predictive value (95% CI). DISCUSSION Changes in biomarkers that can easily be derived from whole blood are useful tools to predict the diagnosis and prognosis of many solid cancers. In this study, we observed significantly higher serum PSA in the PCa group compared with the BPH. However, except for Hb concentration which was significantly lower in the PCa group, this study did not observe significant differences in the full blood count differentials of the PCa group compared BPH group. In comparing serum albumin concentration (ALB) and C-reactive proteins (CRP) as systemic inflammatory markers, significant decrease and increase respectively were observed in the PCa cohort compared with BPH cohort. The mechanisms responsible for these observation remains unclear. However, findings from previous studies support our observations. The reduced serum albumin concentration in PCa patients was earlier reported by Kaya and colleagues [ 23 ] and the reason was not only attributed to malnutrition status but also the existence of inflammation in the host [ 24 ]. As part of systemic inflammatory response to the tumour or from the tumour itself, inflammatory mediators including interleukin-1 (IL-1), interleukin-6 (IL-6), tumour necrosis factor-ɑ (TNFα) and acute phase reactants are released, and as a consequence, there is an increase in transcapillary escape rate of albumin and modulation of albumin synthesis by hepatocytes [ 24 , 25 ]. Thus, albumin level could serve as a good indicator of the presence of PCa, as well as, in the progression of PCa. Furthermore, our findings is consistent with earlier studies on PCa association with CRP. Reports indicate that there is an increased in CRP in response to the presence of the cancer and a further increase during progression of PCa [ 26 ]. The mechanism(s) by which the presence of PCa induce elevated levels of serum CRP is not entirely clear. However, there is general agreement that CRP reflects the cumulative production of proinflammatory cytokines, principally IL-6 [ 27 ] and there is evidence that IL-6 can be produced by prostatic tumours [ 28 ]. IL-6 has also been shown to act as an autocrine growth factor that inhibits apoptosis in prostate cancer [ 29 ]. Finally, the significant reduction in blood haemoglobin concentration (Hb) in PCa group compared with BPH group is consistent with recent report by Kaya et al and Tanno et al. [ 23 , 30 ]. The plausible ascribed mechanism(s) by which the presence of a tumour might leads to low blood Hb could be as result of the induction of the iron-regulatory hormone, hepcidin, by inflammatory cytokines, especially IL-6 [ 31 ]. Elevation of hepcidin by IL-6 leads to hypoferraemia associated with anaemia and iron-restricted erythropoiesis observed in PCa patients [ 32 ]. Having observed these changes, this study therefore aimed at exploring the afore mentioned significant differences observed between PCa and BPH to develop simple differential diagnostic criteria that would predict PCa or BPH, by using the changes in serum total PSA, serum inflammation markers (ALB, CRP) and complete blood count differentials (Hb concentration), to generate ratios for pre-biopsy differential prediction of either PCa or BPH in resource-limited countries. To the best of our knowledge, our analysis is the first attempt to report on the use of ratios involving serum PSA as numerator and ALB, CRP and Hb concentration as denominators to evaluate their potential utility in predicting the presence of either BPH or PCa in suspected patients. Indeed, our results suggest so. Even though the specificity of PSA in diagnosing PCa was low, as also seen in this study (55%, Table 3 b), it use in ratios with the systemic inflammatory variables that changed significantly in the presence of either PCa or BPH enhanced the resultant specificity and their potential utility as differential diagnostic tools. Earlier landmark studies by Stamey et al., (1987) on the ability of serum PSA to diagnose PCa concluded that PSA is elevated in both PCa and BPH, hence could not be used to differentiate one from the other. In an attempt to overcome this challenge, recent studies have reported the predictive diagnostic value of using platelet-to-lymphocyte ratio [ 33 ] and lymphocytes-to-monocytes ratio [ 34 ] values in predicting prostate cancer in suspected patients [ 35 ], whiles others have also reported neutrophil-to-lymphocyte ratio correlate positively with BPH [ 35 ]. In this study, we report the use of PSA and changes in ALB, CRP and Hb in ratios, for the differential diagnostic prediction of PCa and BPH. The mean values of these individual variables in the ratios alone were not discriminatory enough between PCa and BPH groups to merit clinical consideration. As significant as our current findings are, the key limitations are: firstly, the number of patients used in this study was relatively low, especially, number of the patients with BPH. Furthermore, due to the low number of PCa patients, we could not stratify the PCa based on grade to evaluate whether our ratios could predict PCa grade. However, our data are strongly relevant because this is the first study to utilize PSA together with serum inflammatory markers to generate ratios with cut-offs to differentially predict PCa and BPH. CONCLUSIONS Taken together, even though the current preliminary findings suggest that PSA-to-ALB ratio ≥ 1.0, PSA/CRP ratio ˃ 250 and PSA-to-Hb ratio ≥ 2.5 are useful for detecting PCa and differentiate it from BPH is noteworthy, it suffices to state that there is the need for a multi-site study that employs a higher sample size to confirm its general usability as a differential diagnostic tool. Abbreviations PCa Prostate cancer BPH Benign Prostate Hyperplasia ALB Albumin CRP C-Reactive Protein PSA Prostate-Specific Antigen DRE Digital Rectal Examination Hb Hemoglobin concentration Declarations Ethics approval and consent to participate Ethical approval and permission to conduct the study were sought from Committee on Human Research Publication and Ethics of KNUST (CHRPE/AP/629/22) before the study commenced. Written consent was sought from the participants before data collection following the explanation of the purposes, benefits and risks of the study. Participation in the study was voluntary, and confidentiality of participants was ensured throughout the entire process. All the methods of the study were performed in total compliance of the declarations of Helsinki. Consent for publications Not applicable. Availability of data and material Data is available on request to the corresponding author Competing interests The authors declare no conflict of interest. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ Contributions EAN and KAAA developed the concept and designed the study. KAAA, YAM-B and VD collected the data, EAN analysed the data, and EAN , KAAA , GKA and FTD developed the manuscript. GKA , KAAA and FTD revised the draft manuscript. All the authors read and approved the final manuscript. Acknowledgments Not applicable. Authors Information 1 Department of Physiology, School of Medical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi. 2 Division of Urology, Department of Surgery, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi. 3 Soyuz Medical Imaging and Diagnostic Limited, P. O. 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A comprehensive literature review of HALP’s prognostic ability in different cancer types. Oncotarget 14:153–172. https://doi.org/10.18632/oncotarget.28367 Ganz T, Nemeth E (2009) Iron sequestration and anemia of inflammation. Semin Hematol 46:387–393. https://doi.org/10.1053/j.seminhematol.2009.06.001 Yuksel OH, Urkmez A, Akan S, Yldirim C, Verit A (2015) Predictive Value of the Platelet-To-Lymphocyte Ratio in Diagnosis of Prostate Cancer. Asian Pac J Cancer Prev 16:6407–6412. https://doi.org/10.7314/apjcp.2015.16.15.6407 Caglayan V, Onen E, Avci S, Sambel M, Kilic M, Oner S et al (2019) Lymphocyte-to-monocyte ratio is a valuable marker to predict prostate cancer in patients with prostate specific antigen between 4 and 10 ng/dl. Arch Ital Urol Androl 17(4):270–275. 10.4081/aiua.2018.4.270 Kang JY, Choi JD, Cho JM, Yoo TK, Park YW, Lee JH (2021) Association of Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, and Lymphocyte-to-Monocyte Ratio with Benign Prostatic Hyperplasia: A Propensity Score-Matched Analysis. Urol Int 105:811–816. https://doi.org/10.1159/000512894 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4326102","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304148973,"identity":"d406b3a0-e9f9-4d70-99fd-52d3a3f3795a","order_by":0,"name":"Yaw Adjei Mensah-Bonsu","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology School of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yaw","middleName":"Adjei","lastName":"Mensah-Bonsu","suffix":""},{"id":304148974,"identity":"849231b1-519a-49f4-8adf-12b4a86b4b76","order_by":1,"name":"Kwaku Addai Arhin Appiah","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology School of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kwaku","middleName":"Addai Arhin","lastName":"Appiah","suffix":""},{"id":304148975,"identity":"2e4a1268-6a38-4ada-9009-aa24a7579e5a","order_by":2,"name":"Victor Dedjoe","email":"","orcid":"","institution":"Soyuz Medical and Imaging Diagnostics Limited","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"","lastName":"Dedjoe","suffix":""},{"id":304148976,"identity":"6d774e0c-7767-4733-9b58-f4eaf983f52b","order_by":3,"name":"Francis Tanam Djankpa","email":"","orcid":"","institution":"University of Cape Coast School of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"Tanam","lastName":"Djankpa","suffix":""},{"id":304148977,"identity":"8f9e25d1-0a63-4307-9e18-32d4134970f5","order_by":4,"name":"George Kwaw Ainooson","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology Faculty of Pharmacy and Pharmaceutical Sciences","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"Kwaw","lastName":"Ainooson","suffix":""},{"id":304148978,"identity":"c4bc790a-2623-4db2-b0c8-4500b7813b06","order_by":5,"name":"Emmanuel Amankwah Ntim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYLCCBCA2YGA+DOMbAPEBfBoYGyBa2JJBPAnitEBM5jEmTgt/e+/xBw9zGOTN+c98Ni5sq6tjYG/eJsHw6w5OLRJnziU2JG5jMNw5I3dz8sy2wxIMPMfKJBj7nuF21o0cQ5CWBIMbvJsP87YdkGCQyDGTYOw5jFOH/P03UC3nzzwGaqmTYJB/g1+LwQ0eqJYDOczJvG3MQFt4zCQYfuDWYngmx3BG4jYJww030oyNec4dlmzjSSu2SGzArUXu+BmDjz+32cgbnD/8WJqnrI6fn/3wxhsf/uDWAgUSCCYbiEhsI6QDE/whXcsoGAWjYBQMWwAAOSpVIOxslQUAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-8003-1127","institution":"Kwame Nkrumah University of Science and Technology School of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Emmanuel","middleName":"Amankwah","lastName":"Ntim","suffix":""}],"badges":[],"createdAt":"2024-04-25 20:55:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4326102/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4326102/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58872397,"identity":"2692f938-321e-4965-8032-34d6cafa5580","added_by":"auto","created_at":"2024-06-22 20:36:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":576569,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4326102/v1/e803092a-1d7b-41df-ad47-cbdca1440b5f.pdf"}],"financialInterests":"","formattedTitle":"Ratios of Prostate-Specific Antigen to Albumin, C-reactive Protein, and Haemoglobin Concentration are Valuable Markers to Predict Patients with Either Prostate Cancer or Benign Prostate Hyperplasia","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eProstate Cancer (PCa) is a growing concern in Africa according to the International Agency for Research on Cancer (IARC) GLOBOCAN. In sub-Sahara Africa, PCa deaths are predicted to more than double from 47,000 in 2020 to 100,000 by 2040 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This projected increase is partly due to the absence of screening, challenges with early diagnosis, and acute lack of experts and facilities for urological care among others [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore the majority of sub-Saharan Africa (SSA) PCa cases are diagnosed with aggressive disease, often at late stages [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Digital rectal exam (DRE) is more widely used, however, this is not well-accepted by patients, as it is not very sensitive, and unable to detect potentially curable early-stage cancers. Due to these challenges associated with DRE, PCa is often not detected until the disease is at an advanced stage, when symptoms such as pain or urinary problems push patients to seek medical care [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The widespread introduction of serum prostate-specific antigen (PSA) test as a screening tool for PCa enhanced the early detection of PCa and reduced the associated mortality [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, low specificity of PSA for PCa leads to unnecessary biopsies, over-diagnosis and overtreatment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In view of the limitation of DRE and PSA test, guided biopsy detection remains the gold standard for diagnosing PCa [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, this is often not possible because of the cost and limitations in urology (ultrasound-guided biopsies) and biopsy pathology services [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], particularly in rural areas where most of the SSA populations live [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Over the years, PSA-related testing parameters (for example, PSA density, free/total PSA ratio, PSA doubling time, and prostate health index test) have been explored to improve the accuracy of the PSA diagnosis of PCa. However, concerns about the specificity still remains [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, new biomarker(s) with higher specificity to differentially predict PCa from benign conditions to improve diagnosis and clinical decision-making when biopsy (BPx) option is not readily available is urgently needed. It has become increasingly clear that inflammation plays an important role in the development and progression of cancer. Cancer development and progression are dependent on a complex interaction of the tumour and the host inflammatory response [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It is therefore not surprising that changes in the levels of systemic inflammatory markers such as serum albumin and C-reactive protein do occur during the development and progression of a variety of primary operable tumours, including PCa [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Earlier studies have reported that low pre-operative levels of serum albumin predicts lymph node metastases and biochemical recurrence of prostate cancer in radical prostatectomy patients [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Elevated C-reactive protein levels predicts reduced survival and a poor response to chemotherapy in patients with advanced prostate cancer [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, to our knowledge, no study has investigated changes in serum PSA dynamics with systemic inflammatory response variables to differentially predict diagnosis of prostate cancer or benign prostate hyperplasia. The goal of this prospective study was to evaluate the potential use of ratios of serum PSA to pre-treatment serum albumin, C-reactive protein and full blood count differentials to differentially predict diagnosis of prostate cancer or benign prostate hyperplasia in a cohort of pre-biopsy patients.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e \u003cstrong\u003eStudy Population\u003c/strong\u003e \u003cp\u003e Informed consent was sought from participants before involvement in the study. All patients suspected of prostate cancer or BPH who were scheduled for biopsy were eligible based on pre-diagnostic investigations using PSA, ultrasound imaging and digital rectal examinations. Patients with hepatopathy, coagulation-related diseases, inflammatory diseases, autoimmune diseases, cardiovascular and cerebrovascular diseases were excluded. Also, patients with symptomatic prostatitis or urinary tract infection or systemic inflammatory disease or any history of anti-inflammatory drug use within 2 weeks before biopsy (PBx) were excluded. Structured questionnaires were administered and participants were assisted to complete them.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eBlood processing\u003c/strong\u003e \u003cp\u003eAfter completing the questionnaire, 5ml venous blood samples were collected separately into EDTA tube, for full blood count determination and Gel-clot activator tube, for the chemistries. Samples collected into the Gel-clot activator tubes were processed to obtain the serum. Samples in the EDTA tube were run within 24 hours using a 3-part fully automated haematology analyzer.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eBiopsy\u003c/strong\u003e \u003cp\u003eUltrasound-guided prostate biopsies were taken by attending urologists and samples obtained were sent for histopathological examination to determine the presence of tumour and grade (Gleason score) and those that were benign were also recorded.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSerum Prostate Specific Antigen Estimation\u003c/strong\u003e \u003cp\u003eTotal serum PSA was determined using PSA Enzyme Immunoassay test kits according to the manufacturer\u0026rsquo;s protocol. A microplate reader (iMark\u0026trade;, Bio-Rad Laboratories, USA) was used to read the optical density at 450 nm within 15 minutes of colour development.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSystemic Inflammation Assessment (Laboratory assays)\u003c/strong\u003e \u003cp\u003eFull blood cell counts with differential counts were assessed using automated analyzer (Fluorescence flow cytometry, Sysmex 2100). C-reactive protein concentration was measured using a sensitive double antibody sandwich ELISA with rabbit anti-human C-reactive protein and peroxidase-conjugated rabbit anti-human C-reactive protein. The assay was linear from 0.1 to 5 mg/l and logarithmic thereafter. Serum albumin levels were estimated using Bromcresol Green method [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Serum PSA/ Albumin concentration (PSA-to-ALB) ratio, PSA/C-Reactive protein concentration (PSA-to-CRP) ratio, and PSA/Haemoglobin concentration (PSA-to-Hb) ratio were calculated to assess changes in PSA to changes in the measured systemic inflammatory markers. The institutional review board of the Kwame Nkrumah University of Science and Technology approved this study (CHRPE/AP/629/22).\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eBiopsy results, PSA, complete blood count (CBC), Serum biomarkers (C-reactive protein and albumin), PSA-to-CRP ratio, PSA-to-Hb ratio and PSA-to-ALB ratios were compared between PCa and BPH using \u003cem\u003et\u003c/em\u003e-test. Unconditional logistic regression was used to examine the significance of the association between the ratios (PSA-to-ALB ratio, PSA-to-CRP and PSA-to-Hb concentration) with biopsy outcomes (prostate cancer or BPH). Furthermore, univariate and multivariate logistic regression analyses were performed to determine predictors of either BPH or PCa diagnosis. The predictive accuracy of the multivariate model was assessed using receiver operating characteristic (ROC)-derived area under the curve (AUC) analysis. The statistical analysis was performed using Graph pad prism version 5.0.3 and Microsoft excel 2016. A two-tailed \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant for all analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 110 patients who underwent transrectal ultrasound-guided PBx were grouped based on histological finding of the biopsy into BPH (n=35 patients) and PCa (n = 75).\u0026nbsp;The mean age of BPH cohort was 70 years and 67 years for PCa. About half of the total participants had normal BMI: BPH (51.8%) and PCa (47.4%). The majority of the patients recruited for the study were hypertensive (75% of BPH, and 80% of PCa).\u003c/p\u003e\n\u003cp\u003eThe mean serum PSA of the PCa group (176.2 \u0026plusmn; 53.44 ng/ml) was significantly higher than the BPH group (22.55 \u0026plusmn; 4.08 ng/ml). Except for haemoglobin (Hb) concentration which was significantly lower in the PCa group compared with the BPH group, there were no significant differences in the full blood count differentials between the two groups (Tab. 1). Furthermore, the differences in the systemic negative acute inflammatory marker, Albumin (ALB) was significantly lower in the PCa compared with the BPH group. On the other hand, higher mean values of the positive acute inflammatory marker, C-reactive protein, was recorded in the PCa compared with BPH group indicating a differential response of these systemic inflammatory marker responses to BPH and PCa (Tab. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn light of the significant differences observed in serum ALB, Hb concentration and CRP between PCa and BPH groups, further analyses were carried out to investigate ratios involving PSA and the three biomarkers to obtain threshold values that differentiate significantly between PCa and BPH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHere we report on Ratios involving circulating negative and positive acute inflammatory proteins for prognostic threshold, such that the outcome is effectively stratified to differentiate between BPH and PCa. Below in table 2 are findings on the ratios with potential utility in predicting PCa and BPH. \u0026nbsp;The mean PSA-to-ALB ratio was significantly lower in the BPH (0.53 \u0026plusmn; 0.10) group compared with the PCa group (2.867 \u0026plusmn; 0.60) at p ˂ 0.0001. Similarly, mean PSA-to-Hb ratio was significantly lower in the BPH group (1.75 \u0026plusmn; 0.31) compared with the PCa group (11.41 \u0026plusmn; 2.91) at p ˂ 0.0001. Finally, PSA-to-CRP values were significantly lower in the BPH group (181.0 \u0026plusmn; 38.81) compared with the PCa group (435.7 \u0026plusmn; 86.03) at p-value = 0.014. The Receiver Operating Characteristics (ROC) curve analyses were carried out to assess the ability of the ratios to differentially predict PCa or BPH based on sensitivity, specificity, positive predictive value and negative predictive values. Therefore, based on the Area Under the ROC (AUROC) curves analyses, the cut-off points of PSA-to-ALB, PSA-to-CRP and PSA-to-Hb ratios were 1.00, 250 and 2.5 respectively (Tab. 3a). Multivariate analysis showed that PSA-to-CRP (odds ratio (OR) = 2.01 (0.80 - 5.03), PSA-to-Hb (OR = 5.87 (2.27 - 15.16)) and PSA-to-ALB ratio (OR = 12.86 (3.62 - 45.71)) were independent predictors of PCa (Table 3b). The sensitivities, specificities, positive predictive values, and negative predictive values using PSA/CRP cut-off, PSA/Hb cut-off, and PSA/Alb cut-off are shown in Table 3b. Specificity and positive predictive value of PSA-to-ALB ratio was the highest (93% and 91% respectively), followed by PSA-to-Hb ratio (86 %, 80 % respectively) and the least was PSA-to-CRP (78 % and 77 % respectively) (Table 3b).\u003c/p\u003e\n\u003cp\u003eAnalysis of PSA-to-ALB ratio resulted in much significant disparity between PCa and BPH patients with specificity of 93% (81 - 98) and positive predictive value of 91% (77 - 98) at a cut-off of PSA/ALB \u0026ge; 1.0 compared with either PSA alone with specificity of 55% (43 - 68) and PPV of 17% (7 - 34) or Albumin alone with specificity of 61% (49 - 72) and PPV of 17% (7 - 34) from our studies (Tab. 3b). Similarly, a ratio of PSA-to-Hb concentration resulted in much larger discriminating values of specificity 86% (74 - 94) and PPV of 80% (61 - 92) at a cut-off of 2.5 for PCa prediction compared with the individual variables which showed relatively less specificity and PPV (Tab. 3b). Furthermore, our assessment of PSA-to-CRP ratio revealed much significant discriminating values with higher specificity and PPV compared with the individual measured variables. Therefore, it can be concluded that PSA-to-ALB, PSA-to-Hb and PSA-to-CRP resulted in higher disparities between PCa and BPH such that they were effective in stratifying PCa from BPH in our cohort of patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Comparison of serum markers and Full blood count between BPH and PCa groups\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1717056310.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eComparison of serum PSA, Full blood count and selected serum inflammatory markers between benign prostate hyperplasia (BPH) group and prostate cancer (PCa) group. Results are mean \u0026plusmn; SD,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e* signifies\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cem\u003ep\u003c/em\u003e-value \u0026le; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e A comparison of ratios of serum PSA to selected systemic inflammatory markers between Benign prostate hyperplasia (BPH) and Prostate cancer (PCa).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"102%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/Blood Inflammation Marker Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP- value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/ALB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u0026nbsp;\u0026plusmn;\u0026nbsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e0.33 \u0026ndash; 0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e2.867\u0026nbsp;\u0026plusmn;\u0026nbsp;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e1.67 \u0026ndash; 4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/CRP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e181.0 \u0026plusmn;\u0026nbsp;38.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e102.1 \u0026ndash; 259.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e435.7\u0026nbsp;\u0026plusmn;\u0026nbsp;86.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e264.3 \u0026ndash; 607.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" valign=\"top\"\u003e\n \u003cp\u003e0.0145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/Hb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e1.75\u0026nbsp;\u0026plusmn;\u0026nbsp;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e1.13 \u0026ndash; 2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e11.41\u0026nbsp;\u0026plusmn;\u0026nbsp;2.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e6.94 -16.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e A comparison of ratios of serum PSA to selected systemic inflammatory markers between Benign prostate hyperplasia (BPH) and Prostate cancer (PCa). PSA/CRP ratio, serum prostate-specific antigen to C-reactive protein ratio; PSA/ALB \u0026ndash; serum prostate-specific antigen to serum Albumin ratio; PSA/Hb \u0026ndash; serum prostate-specific antigen to Haemoglobin ratio. PCa (n= 75), BPH (n=35). Results are mean + SD,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e* signifies\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cem\u003ep\u003c/em\u003e-value \u0026le; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3a.\u003c/strong\u003e AUROC for variables and PSA-ratios predicting Prostate cancer Biopsy.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariable\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Area (\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSEM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.67 (\u0026plusmn;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.57 - 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eALB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 (\u0026plusmn;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.58 - 0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 (\u0026plusmn;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.59 - 0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 (\u0026plusmn;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.59 - 0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Area (\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSEM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/ALB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.7667 (\u0026plusmn;\u0026nbsp;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 - 0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/CRP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.6453 (\u0026plusmn;\u0026nbsp;0.058)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.53 - 0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.242424242424242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSA/Hb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.7794 (\u0026plusmn;\u0026nbsp;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 - 0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3a:\u0026nbsp;\u003c/strong\u003eData on the Area Under the Receiver Operating characteristic curves (AUROC) for PSA, ALB, CRP and Hb compared with PSA/CRP, PSA/Hb and PSA/ALB ratios to predict PCa. PSA/Hb and PSA/ALB ratios resulted in higher AUROC than the individual variables. PSA - prostate-specific antigen, ALB - Albumin, CRP - C-reactive protein and Hb - haemoglobin concentration\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3b.\u003c/strong\u003e An AUROC analysis and unconditional logistic regression analyses on individual variable and their ratio with PSA to predict prostate cancer biopsy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1717056290.png\" alt=\"image\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;3b\u003c/strong\u003e: AUROC analysis on individual variable and their ratio with PSA to predict prostate cancer biopsy in the study cohort. Unconditional logistic regression analyses assessing the association of individual variables and ratios with Prostate cancer. These studies involved PCa (n=75) cases and BPH (n=35) cases. The specificities, positive predictive values and other predictive values of the ratios showed higher predictive values compared with that of the individual variables. Results are shown as predictive value (95% CI).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eChanges in biomarkers that can easily be derived from whole blood are useful tools to predict the diagnosis and prognosis of many solid cancers. In this study, we observed significantly higher serum PSA in the PCa group compared with the BPH. However, except for Hb concentration which was significantly lower in the PCa group, this study did not observe significant differences in the full blood count differentials of the PCa group compared BPH group. In comparing serum albumin concentration (ALB) and C-reactive proteins (CRP) as systemic inflammatory markers, significant decrease and increase respectively were observed in the PCa cohort compared with BPH cohort.\u003c/p\u003e \u003cp\u003eThe mechanisms responsible for these observation remains unclear. However, findings from previous studies support our observations. The reduced serum albumin concentration in PCa patients was earlier reported by Kaya and colleagues [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and the reason was not only attributed to malnutrition status but also the existence of inflammation in the host [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. As part of systemic inflammatory response to the tumour or from the tumour itself, inflammatory mediators including interleukin-1 (IL-1), interleukin-6 (IL-6), tumour necrosis factor-ɑ (TNFα) and acute phase reactants are released, and as a consequence, there is an increase in transcapillary escape rate of albumin and modulation of albumin synthesis by hepatocytes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Thus, albumin level could serve as a good indicator of the presence of PCa, as well as, in the progression of PCa. Furthermore, our findings is consistent with earlier studies on PCa association with CRP. Reports indicate that there is an increased in CRP in response to the presence of the cancer and a further increase during progression of PCa [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The mechanism(s) by which the presence of PCa induce elevated levels of serum CRP is not entirely clear. However, there is general agreement that CRP reflects the cumulative production of proinflammatory cytokines, principally IL-6 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and there is evidence that IL-6 can be produced by prostatic tumours [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. IL-6 has also been shown to act as an autocrine growth factor that inhibits apoptosis in prostate cancer [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Finally, the significant reduction in blood haemoglobin concentration (Hb) in PCa group compared with BPH group is consistent with recent report by Kaya et al and Tanno et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The plausible ascribed mechanism(s) by which the presence of a tumour might leads to low blood Hb could be as result of the induction of the iron-regulatory hormone, hepcidin, by inflammatory cytokines, especially IL-6 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Elevation of hepcidin by IL-6 leads to hypoferraemia associated with anaemia and iron-restricted erythropoiesis observed in PCa patients [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHaving observed these changes, this study therefore aimed at exploring the afore mentioned significant differences observed between PCa and BPH to develop simple differential diagnostic criteria that would predict PCa or BPH, by using the changes in serum total PSA, serum inflammation markers (ALB, CRP) and complete blood count differentials (Hb concentration), to generate ratios for pre-biopsy differential prediction of either PCa or BPH in resource-limited countries. To the best of our knowledge, our analysis is the first attempt to report on the use of ratios involving serum PSA as numerator and ALB, CRP and Hb concentration as denominators to evaluate their potential utility in predicting the presence of either BPH or PCa in suspected patients. Indeed, our results suggest so. Even though the specificity of PSA in diagnosing PCa was low, as also seen in this study (55%, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), it use in ratios with the systemic inflammatory variables that changed significantly in the presence of either PCa or BPH enhanced the resultant specificity and their potential utility as differential diagnostic tools.\u003c/p\u003e \u003cp\u003eEarlier landmark studies by Stamey et al., (1987) on the ability of serum PSA to diagnose PCa concluded that PSA is elevated in both PCa and BPH, hence could not be used to differentiate one from the other. In an attempt to overcome this challenge, recent studies have reported the predictive diagnostic value of using platelet-to-lymphocyte ratio [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and lymphocytes-to-monocytes ratio [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] values in predicting prostate cancer in suspected patients [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], whiles others have also reported neutrophil-to-lymphocyte ratio correlate positively with BPH [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this study, we report the use of PSA and changes in ALB, CRP and Hb in ratios, for the differential diagnostic prediction of PCa and BPH. The mean values of these individual variables in the ratios alone were not discriminatory enough between PCa and BPH groups to merit clinical consideration.\u003c/p\u003e \u003cp\u003eAs significant as our current findings are, the key limitations are: firstly, the number of patients used in this study was relatively low, especially, number of the patients with BPH. Furthermore, due to the low number of PCa patients, we could not stratify the PCa based on grade to evaluate whether our ratios could predict PCa grade. However, our data are strongly relevant because this is the first study to utilize PSA together with serum inflammatory markers to generate ratios with cut-offs to differentially predict PCa and BPH.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eTaken together, even though the current preliminary findings suggest that PSA-to-ALB ratio\u0026thinsp;\u0026ge;\u0026thinsp;1.0, PSA/CRP ratio ˃ 250 and PSA-to-Hb ratio\u0026thinsp;\u0026ge;\u0026thinsp;2.5 are useful for detecting PCa and differentiate it from BPH is noteworthy, it suffices to state that there is the need for a multi-site study that employs a higher sample size to confirm its general usability as a differential diagnostic tool.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCa\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProstate cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBPH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBenign Prostate Hyperplasia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-Reactive Protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProstate-Specific Antigen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDRE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDigital Rectal Examination\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHb\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHemoglobin concentration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval and permission to conduct the study were sought from Committee on Human Research Publication and Ethics of KNUST (CHRPE/AP/629/22) before the study commenced. Written consent was sought from the participants before data collection following the explanation of the purposes, benefits and risks of the study. Participation in the study was voluntary, and confidentiality of participants was ensured throughout the entire process. All the methods of the study were performed in total compliance of the declarations of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available on request to the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEAN\u003c/strong\u003e and \u003cstrong\u003eKAAA\u003c/strong\u003e developed the concept and designed the study. KAAA, \u003cstrong\u003eYAM-B\u003c/strong\u003e and \u003cstrong\u003eVD\u003c/strong\u003e collected the data, \u003cstrong\u003eEAN\u0026nbsp;\u003c/strong\u003eanalysed the data, and \u003cstrong\u003eEAN\u003c/strong\u003e, \u003cstrong\u003eKAAA\u003c/strong\u003e, \u003cstrong\u003eGKA\u003c/strong\u003e and \u003cstrong\u003eFTD\u003c/strong\u003e developed the manuscript. \u003cstrong\u003eGKA\u003c/strong\u003e, \u003cstrong\u003eKAAA\u003c/strong\u003e and \u003cstrong\u003eFTD\u003c/strong\u003e revised the draft manuscript. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Physiology, School of Medical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi. \u003csup\u003e2\u003c/sup\u003e Division of Urology, Department of Surgery, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi. \u003csup\u003e3\u003c/sup\u003e Soyuz Medical Imaging and Diagnostic Limited, P. O. Box BA 198, Bantama, Kumasi. \u003csup\u003e4\u003c/sup\u003e Department of Physiology, School of Medical Sciences, University of Cape Coast, Cape Coast. \u003csup\u003e1\u0026nbsp;\u003c/sup\u003eDepartment of Pharmacology, Faculty of Pharmacy and Pharmaceutical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdeola HA, Blackburn JM, Rebbeck TR, Zerbini LF (2017) Emerging proteomics biomarkers and prostate cancer burden in Africa. 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Urol Int 105:811\u0026ndash;816. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1159/000512894\u003c/span\u003e\u003cspan address=\"10.1159/000512894\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"benign prostate hyperplasia, biopsy, differential diagnosis, inflammation, prostate cancer","lastPublishedDoi":"10.21203/rs.3.rs-4326102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4326102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProstate Cancer (PCa) diagnosis using PSA alone leads to unnecessary biopsy due to the non-specificity of PSA for PCa. Changes in systemic inflammation variables with the development and progression of PCa cancer have been widely acknowledged. This study evaluated the potential utility of ratios involving changes in serum PSA with changes in systemic inflammatory components: serum albumin, C-reactive protein, and full blood count differentials, to differentially predict PCa biopsy in a cohort of pre-biopsy patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e: We prospectively analyzed data from 110 patients who underwent prostate biopsy between September 2022 and September 2023. Age, PSA, full blood count, serum albumin (ALB), serum C-reactive protein (CRP) and biopsy pathology results of the patients were analyzed. Based on biopsy findings, patients were grouped as benign prostatic hyperplasia (BPH) and PCa.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e: Analyses of ratios involving PSA and the selected inflammatory markers led to wider discriminating values between PCa and BPH. The mean PSA-to-ALB, PSA-to-Hb and PSA-to-CRP ratios were significantly lower in the BPH group compared with the PCa group. AUROC curves analysis at cut-off points of PSA-ALB˃1, PSA-CRP˃250 and PSA-Hb˃2.5 resulted in specificity and positive predictive values for PSA-to-ALB ratio of 93% and 91% respectively, PSA-to-Hb ratio of 86% and 80% respectively and PSA-to-CRP ratio of 78% and 77% respectively. Unconditional regression analysis showed that PSA-to-CRP, PSA-to-Hb and PSA-to-ALB ratios were independent predictors of positive PCa biopsy.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e: This preliminary study suggests that, the combination of PSA with changes in serum inflammatory variables in ratios improved the diagnostic accuracy more than the use of PSA alone. These ratios may assist in the differential prediction of PCa and BPH, especially where biopsy services are not readily available in Low- and Middle-Income countries.\u003c/p\u003e","manuscriptTitle":"Ratios of Prostate-Specific Antigen to Albumin, C-reactive Protein, and Haemoglobin Concentration are Valuable Markers to Predict Patients with Either Prostate Cancer or Benign Prostate Hyperplasia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-30 08:08:34","doi":"10.21203/rs.3.rs-4326102/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff55d1dd-ccc6-48cc-9926-19f31503a0ee","owner":[],"postedDate":"May 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-22T20:28:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-30 08:08:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4326102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4326102","identity":"rs-4326102","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}