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Abstract

Objective

We aimed to investigate the diagnostic value of different laboratory indicators in combination with total prostate-specific antigen (TPSA) for prostate cancer (PCa).

Methods

In this retrospective study, we selected 291 patients who underwent prostate biopsy. Patients were divided into the benign prostatic hyperplasia group and the PCa group. In both groups, patients were again divided into a group with TPSA 4.0–10.0 ng/mL and a group with TPSA >10.0 ng/mL. Clinical data including age, pre-puncture TPSA, free prostate-specific antigen (FPSA), and prostate volume (PV) were collected from all patients. We calculated the metrics PSA/PV (prostate-specific antigen density, PSAD), age/PV (AVR), age × PV/TPSA (PSA-AV), and (FPSA/TPSA)/PSAD [(F/T)/PSAD]). We plotted receiver operating characteristic (ROC) curves and calculated the area under the ROC curve (AUC).

Results

We found statistically significant differences in PV, PSAD, AVR, PSA-AV, and (F/T) PSAD for patients with TPSA 4.0–10.0 ng/mL and TPSA >10 ng/mL. We further plotted the ROC of individual or combined indices in different subgroups and calculated the AUC. We found that the diagnostic efficacy of the combined indices was higher with TPSA >10 ng/mL.

Conclusion

The combination of TPSA with multiple indicators may improve diagnostic accuracy for PCa.

Keywords

Prostate cancer clinical indicator cancer biomarker diagnosis total prostate-specific antigen efficacy

Introduction

Prostate cancer (PCa) is the most common malignancy of the male genitourinary system. In the United States, PCa has the highest incidence among all male malignancies. According to the latest data, there were 268,490 new diagnoses and 34,500 deaths in the United States in 2022.¹ The current gold standard for PCa diagnosis is prostate biopsy (PB). However, this method has some shortcomings, such as a high risk of post-puncture bleeding, infection, and urinary retention. Therefore, a less invasive and more accurate method to diagnose PCa is needed.

Prostate-specific antigen (PSA) is currently used as a validated serum marker for PCa screening, but it has many limitations in distinguishing benign prostatic hyperplasia (BPH) from PCa, with PSA levels in the range of 4.0–10.0 ng/mL referred to as the diagnostic gray area.² Moreover, only approximately 4% of patients with PSA levels <20 ng/mL have PCa. Thus, the diagnostic efficacy of PSA is very different at different PSA levels.³ Use of PSA alone to diagnose PCa may result in a missed diagnosis or misdiagnosed cases. Therefore, PSA remains controversial for the diagnosis of PCa.

The ratio of TPSA values to PV (PSAD) reportedly has better diagnostic efficacy than PSA.⁴ PSAD correlates with the International Society of Urological Pathology classification of PCa and could be considered for inclusion as an indicator for decision-making in the treatment of PCa.⁵ Further, the predictive power of free prostate-specific antigen (FPSA)/TPSA in combination with PSAD is significantly higher than that of PSAD alone.^4,6 Previous experience shows that age and prostate volume (PV) have a potential relationship with the development of PCa. Previous studies have found that calculating the age-to-PV ratio (AVR) is a good predictor when patients are <66 years old.⁷ AVR also has a good predictive effect for patients with PV >30 mL.⁸ Furthermore, by combining age, PV, and TPSA, a novel predictor (PSA-AV) can be calculated, which has better predictive efficacy than PSA alone.⁹

We investigated whether the combination of multiple indicators in the gray diagnostic area of PSA could provide a more accurate diagnosis of PCa. Our study findings may improve the diagnostic accuracy of PCa while reducing invasive diagnostic procedures and provide clinicians with new methods for diagnosing PCa.

Methods

Patients

In this retrospective study, we collected the clinical data of 324 patients who underwent PB for elevated PSA between January 2017 and August 2022 in the Department of Urology, Third Hospital of Hebei Medical University. The indications for BP, as recommended by the Department of Urology of the Chinese Medical Association, were as follows. (1) Digital rectal examination revealing suspicious prostate nodules, with any PSA value. (2) Suspicious lesion found using color ultrasound, computed tomography, or magnetic resonance imaging, with any PSA value. (3) PSA >10.0 ng/mL, with any (F/T) PSA and PSAD values or PSA 4.0–10.0 ng/mL with abnormal (F/T) PSA (calculated as [FPSA/TPSA]/PSAD) or PSAD values. The inclusion criteria were as follows: (1) TPSA >4.0 ng/mL; (2) patients with ultrasound-guided transrectal prostate puncture biopsy and a clear postoperative pathological diagnosis of PCa. The exclusion criteria were (1) patients with pathological findings showing chronic inflammation or high-grade intraprostatic neoplasia; (2) patients with urinary tract infection or obstruction; (3) patients treated with 5α-reductase inhibitors within the previous 2 months; (4) patients who underwent procedures such as cystoscopy, prostate massage, or rectal finger examination 2 weeks prior to PSA testing; (5) patients with any missing information on relevant study data.

The study was approved by the Ethics Committee of the Third Hospital of Hebei Medical University (approval number: K2022-058-1). To protect patient privacy, we eliminated all patient-identifying information. Only de-identified data were used, so the requirement for informed consent was waived. The reporting of this study conforms to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.¹⁰

Case information collection

We collected the patient data required for the study including age, TPSA and FPSA determined using peripheral blood samples (F/T) PSA, PV, and PB pathology. The calculations were as follows: TPSA divided by PV yields PSAD; age divided by PV yields AVR; age multiplied by PV and divided by TPSA yields PSA-AV; and (FPSA divided by TPSA) divided by PSAD yields (F/T)/PSAD.

Statistical analysis

We used SPSS 25.0 to analyze the data (IBM Corp., Armonk, NY, USA). The measurement data were tested for normality using the Kolmogorov–Smirnov test. Normally distributed data are reported as mean ± standard deviation and a t-test was used for comparisons between groups. Comparisons of non-normally distributed indicators were performed using non-parametric tests. We plotted receiver operating characteristic (ROC) curves for individual and combined metrics using MedCalc software version 20.100 to determine the thresholds for the different metrics (MedCalc Software, Ostend, Belgium). The diagnostic value of the relevant indicators for patients with PCa was assessed using the area under the ROC curve (AUC). Differences in the AUC between different indicators were also analyzed. A P-value <0.05 was considered statistically significant.

Results

Patient clinical information

A total of 291 patients met the study criteria, with 142 patients in the BPH group and 149 patients in the PCa group. In each group, patients were further divided according to TPSA level, with 108 patients in the 4.0–10.0 ng/mL group (BPH: 80 patients, PCa: 28 patients) and 183 in the >10.0 ng/mL group (BPH: 62 patients, PCa: 121 patients). In the group with TPSA 4.0–10.0 ng/mL, the mean age of the PCa group was 71.14 ± 10.03 years and that of the BPH group was 70.35 ± 8.61 years. In the group with TPSA >10.0 ng/mL, the mean age of the PCa group was 72.35 ± 8.09 years and that of the BPH group was 78.82 ± 9.22 years. Statistically significant differences were found for PV, PSAD, AVR, PSA-AV, and (F/T)/PSAD in the group with PSA values 4.0–10.0 ng/mL (all P < 0.001). Among them, PSAD and AVR were significantly elevated in patients with PCa whereas PV, PSA-AV, and (F/T)/PSAD were significantly elevated in those with BPH (Table 1).

Table 1.

TPSA 4.0–10.0 ng/mL: analysis of clinical indicators in each patient.

	PCa (n = 28)	BPH (n = 80)	P-value
Age (years) mean ± SD	71.14 ± 10.03	70.35 ± 8.61	0.887
PV (mL)	36.47 (25.28, 58.6)	68.21 (47.32, 96.47)	<0.001
PSAD	0.20 (0.13, 0.28)	0.10 (0.06, 0.14)	<0.001
AVR	1.90 (1.25, 2.92)	1.12 (0.73, 1.54)	<0.001
PSA-AV	355.6 (231.2, 513.3)	684.6 (484.9, 1141)	<0.001
(F/T)/PSAD	0.59 (0.32, 1.53)	1.69 (0.86, 2.92)	<0.001

Values in parentheses are interquartile range.

PCa, prostate cancer; BPH, benign prostatic hyperplasia; TPSA, total prostate-specific antigen; PV, prostate volume; PSAD, prostate-specific antigen density; AVR, age/PV; PSA-AV, age × PV/TPSA; (F/T)/PSAD, (FPSA/TPSA)/PSAD; SD, standard deviation.

In the group with TPSA values >10.0 ng/mL, there were statistically significant differences in age, PV, PSAD, AVR, PSA-AV, and (F/T)/PSAD. Among them, age, PSAD, and AVR were significantly higher in patients with PCa whereas PV, PSA-AV, and (F/T)/PSAD were significantly higher in those with BPH (Table 2). Thus, similar results were found in patients with TPSA 4.0–10.0 ng/mL and those with TPSA >10.0 ng/mL.

Table 2.

TPSA >10.0 ng/mL: analysis of clinical indicators for each patient.

	PCa (n = 121)	BPH (n = 62)	P-value
Age (years) mean ± SD	72.35 ± 8.09	68.82 ± 9.22	<0.01
PV (mL)	40.08 (28.05, 59.82)	80.78 (59.29, 107.7)	<0.001
PSAD	1.88 (0.63, 4.56)	0.18 (0.14, 0.29)	<0.001
AVR	1.71 (1.17, 2.39)	0.84 (0.63, 1.24)	<0.001
PSA-AV	40.49 (15.2, 114.2)	366.3 (217.4, 483.1)	<0.001
(F/T)/PSAD	0.07 (0.01, 0.16)	0.63 (0.38, 1.09)	<0.001

Values in parentheses are interquartile range.

Predictive effect of single or combined indicators for prostate cancer (PCa)

We plotted ROC curves for patients with TPSA 4.0–10.0 ng/mL for TPSA, PSAD, AVR, PSA-AV, (F/T)/PSAD, PV, PSAD + AVR, PSAD + AVR + TPSA, (F/T)/PSAD + PSA-AV, and (F/T)/PSAD +PSA-AV + TPSA (Figure 1). We also calculated the cut-off value, sensitivity, specificity, AUC, and P-values for the different indicators in this subgroup (Table 3). The AUC of TPSA, PSAD, AVR, PSA-AV, (F/T)/PSAD, PV, PSAD + AVR, PSAD +AVR + TPSA, (F/T)/PSAD + PSA-AV, and (F/T)/PSAD + PSA-AV + TPSA was 0.588, 0.775, 0.756, 0.772, 0.781, 0.767, 0.733, 0.774, 0.775, and 0.774, respectively. The results showed that the diagnostic efficacy of TPSA was poor with TPSA 4.0–10.0 ng/mL whereas the diagnostic efficacy of the other indicators was moderate.

Figure 1.

TPSA 4.0–10.0 ng/mL. (a) Diagnostic value of AVR, (F/T)/PSAD, PSA-AV, PSAD, PV, and TPSA alone for prostate cancer. (b) Diagnostic value of different combined indices: PSAD + AVR, PSAD + AVR + TPSA, (F/T)/PSAD + PSA-AV, and (F/T)/PSAD + PSA-AV + TPSA for prostate cancer.

Table 3.

TPSA 4.0–10.0 ng/mL: value of clinical indicators alone or in combination with TPSA for the diagnosis of prostate cancer.

	Cut-off value	Sensitivity	Specificity	AUC	P-value
TPSA	8.15	46.43	76.25	0.588 (0.490–0.682)	0.144
PSAD	0.13	78.57	71.25	0.775 (0.684–0.850)	<0.001
AVR	1.64	64.29	81.15	0.756 (0.664–0.833)	<0.001
PSA-AV	477	75.00	76.25	0.772 (0.681–0.847)	<0.001
(F/T)/PSAD	0.68	64.29	83.75	0.781 (0.691–0.855)	<0.001
PV (mL)	46.05	67.86	76.25	0.767 (0.676–0.843)	<0.001
PSAD + AVR	0.25	67.86	78.75	0.773 (0.682–0.848)	<0.001
PSAD + AVR + TPSA	0.25	67.86	78.75	0.774 (0.683–0.849)	<0.001
(F/T)/PSAD + PSA-AV	0.38	71.43	80.00	0.775 (0.685–0.850)	<0.001
(F/T)/PSAD + PSA-AV + TPSA	0.35	71.43	76.25	0.774 (0.683–0.849)	<0.001

TPSA, total prostate-specific antigen; PV, prostate volume; PSAD, prostate-specific antigen density; AVR, age/PV; PSA-AV, age × PV/TPSA; (F/T)/PSAD, (FPSA/TPSA)/PSAD; AUC, area under the receiver operating characteristic curve.

We plotted ROC curves for patients with TPSA >10.0 ng/mL for TPSA, PSAD, AVR, PSA-AV, (F/T)/PSAD, PV, PSAD +AVR, PSAD + AVR + TPSA, (F/T)/PSAD +PSA-AV, and (F/T)/PSAD + PSA-AV + TPSA (Figure 2). The cut-off value, sensitivity, specificity, AUC, and P-values of the different metrics for this subgroup are shown in Table 4. The AUC of TPSA, PSAD, AVR, PSA-AV, (F/T)/PSAD, PV, PSAD + AVR, PSAD + AVR + TPSA, (F/T)/PSAD +PSA-AV, and (F/T)/PSAD + PSA-AV + TPSA was 0.852, 0.930, 0.826, 0.925, 0.923, 0.805, 0.934, 0.934, 0.930, and 0.923, respectively. The results showed that the diagnostic efficacy of TPSA was moderate with TPSA >10.0 ng/mL; the diagnostic efficacy of most other single indicators was better than that of TPSA. Interestingly, we found the best predictive efficacy for all four combined indicators, with all AUCs reaching 0.9 or more.

Figure 2.

TPSA >10.0 ng/mL. (a) Diagnostic value of AVR, (F/T)/PSAD, PSA-AV, PSAD, PV, and TPSA alone for prostate cancer. (b) Diagnostic value of different combined indices: PSAD + AVR, PSAD + AVR + TPSA, (F/T)/PSAD + PSA-AV, and (F/T)/PSAD + PSA-AV + TPSA for prostate cancer.

Table 4.

TPSA >10.0 ng/mL: value of clinical indicators alone or in combination with TPSA for the diagnosis of prostate cancer.

	Cut-off value	Sensitivity	Specificity	AUC	P-value
TPSA	28.89	74.38	91.94	0.852 (0.793–0.900)	<0.001
PSAD	0.32	91.74	79.03	0.930 (0.883–0.963)	<0.001
AVR	1.47	64.46	90.32	0.826 (0.763–0.878)	<0.001
PSA-AV	141.26	82.64	87.10	0.925 (0.877–0.959)	<0.001
(F/T)/PSAD	0.13	72.73	98.39	0.923 (0.874–0.957)	<0.001
PV (mL)	54	72.73	82.26	0.805 (0.740–0.860)	<0.001
PSAD + AVR	0.58	80.17	91.94	0.934 (0.888 = 0.965)	<0.001
PSAD + AVR + TPSA	0.50	85.95	87.10	0.934 (0.888–0.966)	<0.001
(F/T)/PSAD + PSA-AV	0.83	75.21	95.16	0.930 (0.883–0.962)	<0.001
(F/T)/PSAD + PSA-AV + TPSA	0.71	78.51	90.32	0.923 (0.875–0.957)	<0.001

Comparison of AUC between individual or combined indicators

With TPSA in the range 4.0–10.0 ng/mL, the different predictors were significantly different from TPSA only (P < 0.05). However, TPSA did not show a good predictive effect in this subgroup. The remaining indicators were not significantly different from each other. This suggests that in this patient subgroup, different predictors may not be superior or inferior, except for TPSA (Table 5).

Table 5.

TPSA 4.0–10.0 ng/mL: comparison between different diagnostic indicators.

	TPSA	PSAD	AVR	PSA-AV	(F/T)/PSAD	PV (mL)	PSAD +AVR	PSAD +AVR +TPSA	(F/T)/PSAD +PSA-AV	(F/T)/PSAD +PSA-AV +TPSA
TPSA	N	N	N	N	N	N	N	N	N	N
PSAD	0.001	N	N	N	N	N	N	N	N	N
AVR	0.034	0.575	N	N	N	N	N	N	N	N
PSA-AV	<0.001	0.805	0.698	N	N	N	N	N	N	N
(F/T)/PSAD	0.001	0.852	0.604	0.763	N	N	N	N	N	N
PV (mL)	0.013	0.736	0.526	0.857	0.713	N	N	N	N	N
PSAD + AVR	0.002	0.804	0.539	0.957	0.817	0.746	N	N	N	N
PSAD + AVR +TPSA	0.002	0.889	0.521	0.914	0.837	0.711	0.311	N	N	N
(F/T)/PSAD + PSA-AV	<0.001	0.991	0.655	0.859	0.619	0.790	0.929	0.957	N	N
(F/T)/PSAD +PSA-AV +TPSA	0.002	0.959	0.649	0.925	0.666	0.799	0.970	1.000	0.878	N

TPSA, total prostate-specific antigen; PV, prostate volume; PSAD, prostate-specific antigen density; AVR, age/PV; PSA-AV, age × PV/TPSA; (F/T)/PSAD, (FPSA/TPSA)/PSAD; N, no data available.

With TPSA >10.0 ng/mL, PSAD, PSA-AV, and (F/T)/PSAD were significantly different from other individual indices (TPSA, AVR, and PV) (P < 0.05). In contrast, no significant differences were found between PSAD, PSA-AV, and (F/T)/PSAD. Additionally, we found that when multiple metrics were combined, the differences were significant, in comparison with other single metrics (TPSA, AVR, and PV) (P < 0.001). This suggests that the combined indexes are more effective in predicting PCa (Table 6).

Table 6.

TPSA: >10.0 ng/mL. Comparison between different diagnostic indicators.

	TPSA	PSAD	AVR	PSA-AV	(F/T)/PSAD	PV (mL)	PSAD + AVR	PSAD + AVR + TPSA	(F/T)/PSAD + PSA-AV	(F/T)/PSAD + PSA-AV + TPSA
TPSA	N	N	N	N	N	N	N	N	N	N
PSAD	<0.001	N	N	N	N	N	N	N	N	N
AVR	0.555	<0.001	N	N	N	N	N	N	N	N
PSA-AV	<0.001	0.253	<0.001	N	N	N	N	N	N	N
(F/T)/PSAD	0.003	0.572	0.002	0.849	N	N	N	N	N	N
PV (mL)	0.310	<0.001	0.052	<0.001	<0.001	N	N	N	N	N
PSAD + AVR	<0.001	0.126	<0.001	0.072	0.416	<0.001	N	N	N	N
PSAD + AVR + TPSA	<0.001	0.259	<0.001	0.167	0.425	<0.001	0.828	N	N	N
(F/T)/PSAD + PSA-AV	<0.001	0.914	<0.001	0.292	0.468	<0.001	0.505	0.551	N	N
(F/T)/PSAD + PSA-AV + TPSA	<0.001	0.312	0.003	0.776	0.974	<0.001	0.199	0.219	0.271	N

TPSA, total prostate-specific antigen; PV, prostate volume; PSAD, prostate-specific antigen density; AVR, age/PV; PSA-AV, age × PV/TPSA; (F/T)/PSAD, (FPSA/TPSA)/PSAD; N, no data available.

Discussion

According to current statistics, the incidence of PCa in Asia is the lowest in the world. Compared with the age-standardized rate of PCa incidence in Lithuania at 128.9, China's rate is only 16.8 per 100,000. However, in recent years, the incidence of PCa in China has been on the rise, at approximately 2.6% per year.¹¹

PSA screening is commonly practiced in developed countries; therefore, the incidence of PCa is correspondingly higher.¹² A PSA level of 4.0 ng/mL is clinically considered the threshold value, and clinicians recommend that patients undergo further testing when PSA levels are above 4.0 ng/mL.¹³ However, PSA is not specific to PCa; it can also be elevated in diseases such as BPH and prostatitis.¹⁴ Reportedly, the chance of detecting PCa in patients with PSA 4.0–10.0 ng/mL is only one in four. This indicates that the diagnostic efficacy of PSA values in this range is poor. With PSA greater than 10 ng/mL, the probability of detecting PCa is more than 50%;¹⁵ the results of our study are consistent with this. PSA screening can undoubtedly reduce mortality owing to PCa by detecting PCa earlier. However, PSA testing can also lead to overdiagnosis and overtreatment.¹⁶

Currently, PB remains the gold standard for the diagnosis of PCa. Related studies have hypothesized that an increased number of needle punctures may increase the positivity rate of PCa. However, with an increased number of biopsy puncture sites, the incidence of complications such as bleeding, infection, and urinary retention also increases significantly.¹⁷ Over the span of a decade between 1996 and 2005, the probability of death owing to infection following PB increased from 1% to 4.1%.¹⁸ Therefore, patients require antibiotic treatment after prostate puncture.¹⁹ Although a variety of imaging techniques are available for the early detection of PCa, these are often limited by the high cost of testing, which is passed on to patients. Therefore, more accurate and easier biomarkers are needed to detect PCa.

Researchers have developed a series of new metrics based on patient clinical testing data, with the aim to more accurately predict PCa. These new metrics are thought to have superior predictive power; however, these are often limited by specific items, such as the specific patient age and PV. In patients with BPH, increased PV and irritative prostate symptoms can induce prostate epithelial cell damage, resulting in increased serum TPSA levels. Additionally, if the weight of prostate tissue is increased in patients with PCa, serum PSA will rise accordingly.²⁰ This can lead to a fundamental inability of TPSA to distinguish between PCa and BPH. Therefore, some researchers have proposed the concept of PSAD, the ratio of TPSA to PV, as a way to mitigate the interference caused by PV in PSA.²¹ On this basis, FPSA was included for consideration in our study. We found that (F/T)/PSAD could provide a more precise indication of whether a patient needed further biopsy.^4,22 This could reduce the number of clinically unnecessary PBs and minimize related complications. Additionally, there was a significant correlation between the incidence of PCa and age.²³ Older men, especially those over 65 years of age, have the highest incidence of PCa.²⁴ Whereas there is a negative correlation between PV and PCa incidence, the PV is generally greater in BPH.^25,26 Therefore, we analyzed its predictive ability in PCa by combining age with PV (AVR). AVR has good diagnostic value in patients with PCa of different ages and for PCa in patients <66 years old. At this age, AVR has better diagnostic value than TPSA, FPSA, (F/T) PSA, PSAD, PSA-AV, and (F/T)/PSAD.⁸ A new algorithm (PSA-AV), developed using age, PV, and TPSA, has been found to have similar predictive power to PSAD in PCa, but both are superior to PSA.⁸ It is also recommended to use PSA-AV to predict PCa at age <50 years and PV <20 mL for optimal prediction.²⁷

In our study, we divided TPSA into groups of 4.0–10.0 ng/mL and >10.0 ng/mL. Tables 1 and 2 show that patients in these two groups had similar results, with higher PSAD and AVR levels in patients with PCa whereas PV, PSA-AV, and (F/T)/PSAD levels were lower. Patients with PCa and TPSA >10.0 ng/mL were older, suggesting that age may be a potential risk factor in patients with TPSA >10.0 ng/mL.

We plotted ROC curves for different individual metrics and analyzed the AUC values. The results in Table 3 and Figure 1 suggest that the predictive power of TPSA at 4.0–10.0 ng/mL is very poor, which is similar to the results of other studies. However, the predictive power of PSAD, AVR, PSA-AV, (F/T)/PSAD, and PV were generally similar, with AUCs above 0.7. Our finding suggests that these indicators have better predictive power in this patient subgroup. Additionally, we used each of these indicators in combination with TPSA for the prediction of PCa; the AUCs were greater than 0.7, showing that the predictive ability of these indicators was greater than that of TPSA alone. We further analyzed differences between the different diagnostic indicators AUC (Table 5). Both single and combined indicators for the prediction of PCa were significantly different from TPSA; however, there was no significant difference between them. This suggests that there may be no difference in predictive power between the individual or combined metrics in this patient subgroup, except for TPSA. The results in Table 4 and Figure 2 show that with TPSA >10.0 ng/mL, the predictive power of TPSA was significantly improved compared with that in the subgroup with TPSA 4.0–10.0 ng/mL, reaching an AUC of 0.852. The AUC of PV and AVR were above 0.8 whereas the AUCs of PSAD, PSA-AV, and (F/T)/PSAD were all above 0.9, which suggests that these metrics have superior predictive power in this subgroup. Additionally, we used each of these indicators in combination with TPSA for the prediction of PCa. The AUCs of the combined indicators were generally higher in comparison with the single indicators. We further analyzed differences between AUCs of the different diagnostic indicators (Table 6). We found that combined indicators generally had greater differences as compared with the single indicators, which suggests that the combined indexes are more predictive of PCa when TPSA is >10.0 ng/mL.

This study has the following limitations. This was a retrospective study with a limited number of participants; thus, there is a possibility of selection bias. The accuracy of our findings needs to be further verified in prospective studies. Additionally, the data collected in this study were mainly from single-center studies. Therefore, our results should be further evaluated using multicenter data with a large sample size. Finally, owing to the small sample size, the critical values, sensitivity, and specificity of the relevant parameters, as well as other relevant indicators need to be further analyzed.

In conclusion, this study showed that the predictive power of different indicators was stronger than that of TPSA with TPSA values between 4.0 and 10.0 ng/mL. However, with TPSA >10.0 ng/mL, the predictive ability of the combined indexes was stronger. These findings can provide a clinical reference for the diagnosis of PCa, thereby reducing unnecessary prostate puncture.

Footnotes

Acknowledgement

We thank Nurse Lee for her help in collecting data for us.

Author contributions

Qingxu Zhang, Haodong Li, and Jianguo Ma drafted the overall design of the paper. Zhiguo Song, Shaopeng Kong, and Sitao Zhao collected and organized the data. Siqi Fan and Fei Qin prepared the images. Qingxu Zhang and Haodong Li organized the study data, data analysis and wrote the initial draft of the paper. All authors participated in reviewing the article content.

Data availability

The data used to support the findings of this study are available from the corresponding author upon reasonable request.

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

This study was supported by the Hebei Provincial Excellent Talents in Clinical Medicine Project (2022180).

ORCID iD

Haodong Li

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Potential diagnostic value of multiple indicators combined with total prostate-specific antigen in prostate cancer

Abstract

Objective

Methods

Results

Conclusion

Keywords

Introduction

Methods

Patients

Case information collection

Statistical analysis

Results

Patient clinical information

Predictive effect of single or combined indicators for prostate cancer (PCa)

Comparison of AUC between individual or combined indicators

Discussion

Footnotes

Acknowledgement

Author contributions

Data availability

Declaration of conflicting interest

Funding

ORCID iD

References