Introduction
Colorectal cancer (CRC) is a major threat to human health. According to the 2020 Global Cancer Statistics, the incidence of CRC ranks fifth globally.1 Current investigations show that 70–90% of CRCs originate from adenomas and 10–20% evolve from serrated polyps.2 Therefore, the early detection of colorectal adenomas is important for CRC screening. Colonoscopy is an effective method of screening for colorectal adenomas. Studies have shown that colonoscopy screening reduces the incidence of CRC by 18–26% and the mortality rate by 22–31%3–7; however, the acceptance of endoscopy by patients affects the screening effect to some extent.
A 10-year population-based multicenter study showed that the acceptance rate of the fecal occult blood test (FOBT) was significantly higher than that of colonoscopy among the population (34.25% vs. 25.38%, P < 0.001), and the acceptance rate of colonoscopy was even lower among older individuals with a high risk of colon cancer.8 Many regions have established a two-step screening method, a screening strategy for selecting high-risk groups for CRC through the establishment of a risk model and then performing colonoscopy. Two-step risk models usually include demographic risk factors such as the Asia-Pacific Colorectal Screening Scoring System (APCS).9,10 In addition, risk stratification models include FOBT and fecal DNA testing11–13; however, no study has provided clinical data for risk models that combine fecal syndecan-2 (SDC2) methylation testing.
SDC2 is located on human chromosome 8 (chr8:96,493,813–96,611,790) and encodes syndecan-2. It affects the proliferation and invasion of colon cancer cells by regulating their adhesion.14,15 Research has shown that, compared with normal tissues, the SDC2 gene exhibits higher levels of methylation at different stages of CRC and some adenoma tissues, and its expression in CRC and some adenoma tissues is also significantly higher than that in normal tissues, demonstrating its high diagnostic value.16 Therefore, detecting the methylation level of SDC2 in feces theoretically helps to diagnose colonic adenomas and colon cancer. Previous studies have confirmed that SDC2 methylation has good sensitivity and specificity for detecting CRC or advanced adenomas.17,18
This study employed colonoscopy and histopathological examination as reference standards to conduct a multicenter diagnostic trial across six medical institutions, aiming to evaluate the sensitivity and specificity of the fecal double-fragment SDC2 methylation test for CRC screening, refine the existing risk stratification scoring system, and validate its clinical utility.
Materials and methods
Study design
This study employed a prospective multicenter diagnostic research design and was approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang Chinese Medical University (approval number: 2023-KLS-128-02); this approval covered all participating sites. This study adhered to the Declaration of Helsinki (as revised in 2024). Written informed consent was obtained from all participants. From August 2023 to February 2024, participants who met the inclusion criteria initially underwent fecal double-fragment SDC2 methylation testing, followed by colonoscopy. During the colonoscopic procedure, polyps were removed upon obtaining written informed consent from the participants or their legally authorized representatives and were subsequently subjected to histopathological examination. Colonoscopy findings, combined with histopathological results, were used as reference standards to evaluate the performance of fecal double-fragment SDC2 methylation testing. A novel risk stratification scoring system was developed by integrating the results of fecal double-fragment SDC2 methylation testing with the APCS, and discriminatory and stratification efficacies were assessed.
Participants
Participants were enrolled consecutively and simultaneously from six medical institutions in Zhejiang Province, China, between August 2023 and February 2024. The participating institutions included the First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Anji County Hospital of Traditional Chinese Medicine, Quzhou Hospital of Traditional Chinese Medicine, Zhejiang Jin Hua Guang Fu Tumor Hospital, Hengdian Wenrong Hospital, and Jiaxing Xiuzhou District People’s Hospital.
The participants were screened according to the following eligibility criteria. Inclusion criteria included: (1) age ≥ 18 years; (2) ability to provide a fresh fecal sample weighing > 2.5 g; and (3) no history of colonoscopy within the past three years. Exclusion criteria were as follows: (1) severe hepatic or cardiopulmonary dysfunction, coagulation or bleeding disorders, or recent use (within one week) of medications affecting the coagulation system that would contraindicate colonoscopy; (2) presence of watery stools; (3) confirmed diagnosis of Crohn’s disease or ulcerative colitis with routine surveillance colonoscopies for inflammatory bowel disease; and (4) prior surgical intervention or other treatments for CRC.
Test methods
Prior to colonoscopy, participants collected fresh stool samples using the provided stool sampling kit, recorded demographic information (including patient ID, sex, and age) on the designated sampling card, and completed a case report form to document their medical history, including diabetes status, smoking and alcohol consumption, and family history of CRC.
The SDC2 methylation test was performed by a certified third-party medical laboratory, and the laboratory personnel for SDC2 were blinded to the colonoscopy and histology results. The fecal sampling kit with sample preservation solution (stored at room temperature and stable for up to seven days) and the human SDC2 methylation detection kit were supplied by AI WEI KE BIOTECH Co., Ltd. In accordance with the testing protocol provided by the laboratory, the SDC2 methylation assay consisted of the following four steps (for more details, please refer to the supplement file “Laboratory SOP”): (1) extraction of DNA from fecal samples, (2) bisulfite conversion of DNA, (3) polymerase chain reaction-based detection, and (4) result interpretation. A test result was considered negative if the ΔCt value in reaction solution A was ≥10.0 and the ΔCt value in reaction solution B was ≥10.5; otherwise, the result was considered positive.
Following the collection of fecal samples, the participants underwent bowel preparation prior to colonoscopy. Bowel cleansing was performed using 3,000 mL of isotonic full-bowel irrigation solution. The efficacy of bowel preparation was assessed during colonoscopy using the Boston Bowel Preparation Scale. The scores for the right, transverse, and left colons were all above 2 points, indicating adequate bowel preparation. The procedures were conducted using an Olympus HQ290AZI colonoscope, with a minimum withdrawal time of at least 6 m, a cecal intubation rate of at least 90%, and an adenoma detection rate of at least 20% (25% for men and 15% for women) set as quality metrics.19 If colonoscopy findings indicated the presence of polyps, the endoscopists removed the polyps after obtaining written consent from the patient or their legally authorized representative. Histopathological evaluations were independently conducted by the Pathology Department of each participating institution. Throughout this process, both endoscopists and pathologists were blinded to the SDC2 methylation test results.
Classification criteria
Based on the test results, samples were classified as negative or positive for SDC2 methylation. According to the colonoscopic findings, individuals were categorized as having polyps (polyp-positive) or without polyps (polyp-negative). Polyps were further classified into hyperplastic polyps, adenomas, advanced adenomas, and carcinomas, based on histopathological evaluation. Adenomas meeting at least one of the following criteria were defined as advanced adenomas, which was pre-specified in the protocol20: (1) size ≥ 1 cm; (2) presence of high-grade intraepithelial neoplasia; (3) villous or tubulovillous architectural components.
Statistical analysis
Sample size estimation
The sample size was determined using the following formula:
n (base on sensibility)=Z1−α/2×SN×(1−SN)L2×Prevalence
According to clinical research of the Human Fecal Double Fragment SDC2 Gene Methylation Detection Kit (fluorescence polymerase chain reaction method), the assay demonstrated a sensitivity (SN) of 66.1% for detecting advanced adenomas and CRC in asymptomatic individuals, with a specificity (SP) of 90.1%. Based on previous data from our medical center,21 the prevalence of colorectal adenomas among individuals undergoing colonoscopy was 25.8%, with advanced adenoma accounting for 8.3% and CRC detected in 0.6% of cases. The allowable margin of error (L) was set at 0.1, and the significance level (α) was established at 0.05. Based on sensitivity and specificity calculations, the required sample size was no less than 746 cases.
Risk factors and kappa analysis
Data were analyzed using SPSS version 25.0. Normally distributed measurement data are presented as mean ± standard deviation and were compared using the independent samples t-test. Non-normally distributed measurement data are expressed as medians (interquartile ranges) and were analyzed using the Mann–Whitney U test. Categorical variables, including rates and constituent ratios, are expressed as N (%) and were compared using the chi-square test or Fisher’s exact test, as appropriate. The Kappa statistic was used to assess the agreement between the SDC2 methylation detection results and colonoscopic findings. Concurrently, the sensitivity, specificity, positive predictive value, and negative predictive value were calculated.
Model establishment and validation
This study employed a development-validation research design. During the model development phase, 632 participants were included, and data from an independent, randomly selected sample of 316 participants were used in the external validation set.
The RAND function in Excel was used to randomly select samples for model development. Ordered logistic regression was used to assess the effects of the predictor variables and assign the corresponding scores. Bootstrap optimism correction (n = 200) was used to evaluate model performance using the receiver operating characteristic curve and area under the curve (AUC). The Youden index and corresponding optimal cutoff values were determined.22 The statistical significance of the differences in AUC values was assessed using the DeLong test. The calibration performance of the development set (n = 632) was evaluated via bootstrap optimism correction (B = 200) using the “rms” package in R 4.5.2. The calibration performance of the validation set was evaluated by directly applying the coefficients of the development set model to the validation set data (n = 316) and generating a scatter plot of the predicted versus observed probabilities. The calibration intercept represents the overall accuracy of the predicted risk, and the calibration slope represents the appropriateness of the predicted risk range.
Results
Patient characteristics
A total of 985 participants were recruited who underwent both fecal SDC2 methylation kit testing. All SDC2 test results were valid, with all participants demonstrating adequate bowel preparation and undergoing complete colonoscopy. During the period between fecal collection and colonoscopy, no new medical treatments were initiated for the participants, and patients with diabetes continued their original blood sugar management regimens. Polyps were detected in 462 individuals, among whom 37 did not undergo polypectomy or pathological examination at the medical centers involved in this study. These participants were included in the polyp detection rate; however, they were not included in the estimated risk factors and the APCS-SDC2 scoring system. A total of 425 patients underwent endoscopic polypectomy and pathological examinations. The pathological types of the polyps are shown in Figure 1. There were 204 cases of adenomas, with a detection rate of 20.7%, and 80 cases of advanced adenomas, with a detection rate of 8.1%.
The risk factors for polyps, adenomas, and advanced adenomas were analyzed individually. The results of the univariate and multivariate logistic regression analyses are presented in Table 1. Age, male sex, and smoking history were identified as independent risk factors for polyps. Independent risk factors for adenomas included age, male sex, smoking history, and family history of CRC. Age, male sex, and a family history of CRC were identified as independent predictors of advanced adenomas.
Table 1Risk factors for polyp, adenoma, and advanced adenoma
| Polyps | Univariate analysis
| Multivariate analysis
|
|---|
| Positive (n = 462) | Negative (n = 523) | P | OR (95% CI) | P |
|---|
| APCS score | 2.43 ± 1.23 | 1.79 ± 1.18 | <0.001 | | |
| Age | 57.9 ± 9.6 | 53.1 ± 10.5 | <0.001 | 1.046 (1.032–1.060) | <0.001 |
| Sex | | | <0.001 | 1.684 (1.274–2.225) | <0.001 |
| Female | 212 (39.3%) | 328 (60.7%) | | | |
| Male | 250 (56.2%) | 195 (43.8%) | | | |
| Smoke | | | <0.001 | 2.067 (1.105–3.865) | 0.023 |
| Yes | 71 (74.1%) | 24 (25.3%) | | | |
| No | 391 (43.9%) | 499 (56.1%) | | | |
| Drink | | | <0.001 | 1.486 (0.775–2.852) | 0.233 |
| Yes | 59 (72.8%) | 22 (27.2%) | | | |
| No | 403 (44.6%) | 501 (55.4%) | | | |
| Diabetes | | | 0.072 | | |
| Yes | 20 (62.5%) | 12 (37.5%) | | | |
| No | 442 (46.4%) | 511 (53.6%) | | | |
| Family history of CRC | | | 0.005 | 1667743611 (0-/) | 0.999 |
| Yes | 7 (100%%) | 0 (0%) | | | |
| No | 455 (46.5%) | 523 (53.5%) | | | |
| Boston score | 7.46 ± 0.86 | 7.51 ± 0.82 | 0.195 | | |
| Right colon | 2.48 ± 0.50 | 2.47 ± 0.50 | 0.615 | | |
| Transverse colon | 2.47 ± 0.50 | 2.54 ± 0.50 | 0.665 | | |
| Left colon | 2.51 ± 0.50 | 2.50 ± 0.50 | 0.829 | | |
| Adenoma | Univariate analysis
| Multivariate analysis
|
|---|
| Positive (n = 264) | Negative (n = 684) | P | OR (95% CI) | P |
|---|
| APCS score | 2.56 ± 1.20 | 1.91 ± 1.21 | <0.001 | | |
| Age | 58.7 ± 9.5 | 54.0 ± 10.4 | <0.001 | 1.045 (1.029–1.061) | <0.001 |
| Gender | | | <0.001 | 1.578 (1.147–2.172) | 0.005 |
| Female | 116 (22.2%) | 407 (77.8%) | | | |
| Male | 148 (34.8%) | 277 (65.2%) | | | |
| Smoke | | | <0.001 | 2.036 (1.118–3.707) | 0.020 |
| Yes | 49 (52.7%) | 44 (47.3%) | | | |
| No | 215 (25.1%) | 640 (74.9%) | | | |
| Drink | | | <0.001 | 1.283 (0.683–2.411) | 0.438 |
| Yes | 39 (49.4%) | 40 (50.6%) | | | |
| No | 225 (25.9%) | 644 (74.1%) | | | |
| Diabetes | | | 0.015 | 1.629 (0.768–3.453) | 0.203 |
| Yes | 15 (46.9%) | 17 (53.1%) | | | |
| No | 249 (27.2%) | 667 (72.8%) | | | |
| Family history of CRC | | | 0.008 | 13.637 (1.554–119.682) | 0.018 |
| Yes | 5 (83.3%) | 1 (16.7%) | | | |
| No | 259 (27.5%) | 683 (72.5%) | | | |
| Boston score | 7.44 ± 0.85 | 7.49 ± 0.84 | 0.782 | | |
| Right colon | 2.48 ± 0.50 | 2.7 ± 0.50 | 0.564 | | |
| Transverse colon | 2.46 ± 0.50 | 2.53 ± 0.50 | 0.358 | | |
| Left colon | 2.50 ± 0.50 | 2.49 ± 0.50 | 0.812 | | |
| Advanced adenoma | Univariate analysis
| Multivariate analysis
|
|---|
| Positive (n = 80) | Negative (n = 868) | P | OR (95% CI) | P |
|---|
| APCS score | 2.95 ± 0.99 | 2.01 ± 1.23 | <0.001 | | |
| Age | 61.4 ± 9.2 | 54.8 ± 10.3 | <0.001 | 1.068 (1.041–1.095) | <0.001 |
| Gender | | | <0.001 | 2.165 (1.269–3.693) | 0.005 |
| Female | 29 (5.5%) | 494 (94.5%) | | | |
| Male | 51 (12.0%) | 374 (88.0%) | | | |
| Smoke | | | <0.001 | 1.646 (0.725–3.737) | 0.234 |
| Yes | 17 (18.3%) | 76 (81.7%) | | | |
| No | 63 (7.4%) | 792 (92.6%) | | | |
| Drink | | | 0.007 | 1.097 (0.453–2.656) | 0.837 |
| Yes | 13 (16.5%) | 66 (83.5%) | | | |
| No | 67 (7.7%) | 802 (92.3%) | | | |
| Diabetes | | | 0.137 | - | - |
| Yes | 5 (15.6%) | 27 (84.4%) | | | |
| No | 75 (8.2%) | 841 (91.8%) | | | |
| Family history of CRC | | | <0.001 | 16.531 (3.027–90.288) | 0.001 |
| Yes | 3 (50%) | 3 (50%) | | | |
| No | 77 (8.2%) | 865 (91.8%) | | | |
| Boston score | 7.54 ± 0.83 | 7.47 ± 0.84 | 0.703 | | |
| Right colon | 2.56 ± 0.50 | 2.46 ± 0.50 | 0.244 | | |
| Transverse colon | 2.46 ± 0.50 | 2.51 ± 0.50 | 0.160 | | |
| Left colon | 2.51 ± 0.50 | 2.49 ± 0.50 | 0.806 | | |
Diagnostic effect
Pathological examination served as the reference standard for evaluating the diagnostic sensitivity and specificity of fecal SDC2 methylation for the identification of colon polyps, adenomas, and advanced adenomas. The results demonstrated that the sensitivity of fecal double-fragment SDC2 methylation detection for advanced adenomas was 31.3%, with a specificity of 96.1%, a positive predictive value of 42.4%, and a negative predictive value of 93.8%. Kappa consistency analysis indicated a statistically significant agreement between fecal SDC2 methylation testing and the reference standard for the detection of polyps, adenomas, and advanced adenomas (P < 0.001), as detailed in Table 2.
Table 2The diagnostic performance of the fecal SDC2 Methylation test
| Polyps | Colonoscopy combined with pathology
| Kappa value (95% CI) | P |
|---|
| Positive | Negative | |
|---|
| SDC2 | Positive | 49 | 13 | 79.0% (66.5–87.9%)c | 0.086 (0.05, 0.12) | <0.001 |
| Negative | 413 | 510 | 55.3% (52.0–58.5%)d | | |
| | 10.6% (8.0–13.9%)a | 97.5% (95.7–98.6%)b | | | |
| Adenoma | Colonoscopy combined with pathology
| Kappa value (95% CI) | P |
|---|
| Positive | Negative | |
|---|
| SDC2 | Positive | 32 | 27 | 54.2% (40.8–67.1%)c | 0.107 (0.05, 0.16) | <0.001 |
| Negative | 232 | 657 | 73.9% (70.9–76.7%)d | | |
| | 12.1% (8.6–16.8%)a | 96.1% (94.2–97.3%)b | | | |
| Advanced adenoma | Colonoscopy combined with pathology
| Kappa value (95% CI) | P |
|---|
| Positive | Negative | |
|---|
| SDC2 | Positive | 25 | 34 | 42.4% (29.8–55.9%)c | 0.310 (0.20, 0.42) | <0.001 |
| Negative | 55 | 834 | 93.8% (92.0–95.3%)d | | |
| | 31.3% (21.6–42.7%)a | 96.1% (94.6–97.2%)b | | | |
APCS-SDC2 scoring system
By integrating the SDC2 test results with the APCS score, we developed a novel scoring system, termed APCS-SDC2, which incorporates age, sex, smoking status, family history, and SDC2 test results, as presented in Table 3. A total of 632 samples were randomly selected to develop the scoring system, and 316 samples were used to validate the performance of the model.
Table 3APCS-SDC2 scoring system
| Risk factor | Categories | Points |
|---|
| Age | <50 | 0 |
| 50–69 | 2 |
| ≥70 | 3 |
| Gender | Female | 0 |
| Male | 1 |
| Smoke | No | 0 |
| Yes | 1 |
| Family history | No | 0 |
| Yes | 2 |
| Fecal SDC2 test | Negative | 0 |
| Positive | 2 or 3* |
Receiver operating characteristic curves were used to assess the risk prediction performance of the APCS-SDC2 system. First, in the development set: (1) for adenomas, the apparent AUC of the APCS-SDC2 score was 0.6899 (95% confidence interval (CI): 0.644–0.7358), and the corrected AUC was 0.6879 after bootstrap optimism correction (mean optimism = 0.002). The apparent AUC of the APCS score was 0.682 (95% CI: 0.6365–0.7275, DeLong P = 0.2016). (2) For advanced adenomas, the apparent AUC of the APCS-SDC2 score was 0.7917 (95% CI: 0.7311–0.8523), and the corrected AUC was 0.7915 after bootstrap optimism correction (mean optimism = 0.0002). The apparent AUC of the APCS was 0.7523 (95% CI: 0.6971–0.8074, DeLong P = 0.0047). Second, in the independent validation set: (1) for adenomas, the apparent AUC of the APCS-SDC2 score was 0.6099 (95% CI: 0.5429–0.6769), and the apparent AUC of the APCS score was 0.5888 (95% CI: 0.5224–0.6553, DeLong P = 0.0676). (2) For advanced adenomas, the apparent AUC of the APCS-SDC2 score was 0.7032 (95% CI: 0.5869–0.8195), and the apparent AUC of the APCS score was 0.6228 (95% CI: 0.5113–0.7343, DeLong P = 0.0583), as shown in Figure 2.
In the model developed to identify individuals at risk of adenomas, the calibration plot of the development set displayed favorable calibration characteristics (calibration slope = 1.0), and the calibration performance remained stable in the external validation set (calibration intercept = 0.021, calibration slope = 0.591). Similarly, after calibrating the model to identify individuals at high risk for advanced adenomas, the calibration plot of the development set demonstrated good calibration characteristics (calibration slope = 1.0), and the calibration performance remained stable in the external validation set (calibration intercept = −0.014, calibration slope = 0.695). This indicated that the predicted probabilities of the model exhibited good consistency across different populations, as shown in Figure 3.
The optimal cutoff value for the APCS score in adenoma screening was determined to be 2 points, yielding a sensitivity of 80% and a specificity of 31.9%. For the APCS-SDC2 score, the corresponding cutoff value was 4 points, with a significantly lower sensitivity of 36.4% (P < 0.001) and a higher specificity of 76.3% (P < 0.001). In the detection of advanced adenomas, the APCS score demonstrated an optimal cutoff of 3 points, achieving a sensitivity of 50% and a specificity of 66.7%. For the APCS-SDC2 score, the cutoff value was set at 5 points, resulting in a sensitivity of 36.4% (P = 0.361) and a significantly higher specificity of 86.7% (P < 0.001), as shown in Table 4. The clinical reclassification tables versus APCS showed that when the APCS score was 2, a positive SDC2 indicated a transition from low risk to high risk of advanced adenomas (Table 5). No adverse events were observed during the study period.
Table 4Consistency test based on the scoring system
| Adenoma | Colonoscopy combined with pathology
| Kappa value (95% CI) | P |
|---|
| Positive | Negative | |
|---|
| APCS | Positive | 72 | 154 | 31.9% (25.8–38.4%)c | 0.082 (0.009, 0.155) | 0.035 |
| Negative | 18 | 72 | 80% (70.2–87.7%)d | | |
| | 80% (70.2–87.7%)a | 31.9% (25.8–38.4%)b | | | |
| APCS_SDC2 | Positive | 43 | 47 | 47.8% (37.1–58.6%)c | 0.133 (0.023, 0.243) | 0.016 |
| Negative | 75 | 151 | 66.8% (60.3–72.9%)d | | |
| | 36.4% (27.8–45.8%)a | 76.3% (69.7–82%)b | | | |
| Advanced adenoma | Colonoscopy combined with pathology
| Kappa value (95% CI) | P |
|---|
| Positive | Negative | |
|---|
| APCS | Positive | 11 | 98 | 10.1% (5.1–17.3%)c | 0.059 (−0.019, 0.137) | 0.113 |
| Negative | 11 | 196 | 94.7% (90.7–97.3%)d | | |
| | 50% (28.2–71.8%)a | 66.7% (61–72%)b | | | |
| APCS_SDC2 | Positive | 8 | 39 | 17% (7.6–30.8%)c | 0.151 (0.014, 2.88) | 0.003 |
| Negative | 14 | 255 | 94.8% (91.4–97.1%)d | | |
| | 36.4% (17.2–59.3%)a | 86.7% (82.3–90.4%)b | | | |
Table 5Clinical reclassification tables versus APCS
| APCS Point | Adenoma
| Advanced adenoma
|
|---|
| APCS | Plus SDC2 | APCS | Plus SDC2 |
|---|
| 1 | low risk | low risk | low risk | low risk |
| 2 | high risk | high risk | low risk | high risk |
| ≥3 | high risk | high risk | high risk | high risk |
Discussion
The prognosis of CRC is influenced by tumor stage, with the five-year survival rate decreasing as the tumor progresses. Early diagnosis and treatment are key to the management of colon cancer.23 Research has shown that most CRCs originate from adenomas, and adenoma screening is an important means of reducing the incidence of colon cancer.4 Significant changes in gene expression occur during the occurrence and development of CRC, such as the overactivation of proto-oncogenes and the inactivation of tumor suppressor genes.24,25 Fecal DNA testing is a new detection method that combines gene sequencing technology.26,27 Detection of specific gene fragments may improve the specificity of screening for colon adenomas and colon cancer and is a promising noninvasive method for screening CRC and adenomas.
Previous studies have shown significant differences in the methylation levels of SDC2 between colon cancer tissues and adjacent tissues.16 A detection kit developed based on this method has achieved positive results in previous clinical diagnostic studies.17,28 A 2022 study indicated that the sensitivity of fecal SDC2 and SFRP2 gene detection in CRC was 92.9%.29 Many studies have demonstrated the screening role of noninvasive tests, such as the FOBT and fecal immunochemical test (FIT), in CRC. Some studies have also established a modified APCS combined with noninvasive tests to enhance stratification ability.30–32 Subsequent studies have shown that the combination of fecal DNA testing (SDC2 and SFRP2), FOBT, FIT, and APCS scores increases the detection rate of advanced adenomas (95.2% of CRC and 73.5% of advanced adenomas).13 A meta-analysis demonstrated that the true positive rate of advanced adenomas detected through FIT screening was 6.6% (5.2–7.7%),33 which was lower than the outcome of fecal SDC2 detection (42.4%, 95% CI: 29.8–55.9%). Moreover, research has revealed that the sensitivity of the APCS score in combination with FIT for advanced adenoma was 28% (7/25),34 which was also lower than that of the APCS-SDC2 scoring system (31.3%, 95% CI: 21.6–42.7%).
Our results showed that the independent risk factors for colonic polyps, adenomas, and advanced adenomas were similar. In this study, the adenoma detection rate was 20.7%, which met the quality assessment criteria,35 and the endoscopic results were reliable. The population with positive fecal SDC2 methylation had a higher detection rate of polyps (odds ratio (OR) = 4.014, 95% CI: 2.091–7.707, P < 0.001), adenomas (OR = 2.806, 95% CI: 1.601–4.918, P < 0.001), and advanced adenomas (OR = 9.554, 95% CI: 5.137–17.770, P < 0.001). We further investigated the role of the fecal double-fragment SDC2 test in population screening and established an APCS-SDC2 scoring system by combining the results of the fecal SDC2 methylation detection. The internal validation results showed that the modified APCS scoring system based on the SDC2 test results had better discrimination of colon polyps, adenomas, and advanced adenomas than the original APCS scoring system. Therefore, the introduction of SDC2 test results as a risk factor improved the ability of the model to distinguish high-risk populations for intestinal polyps, adenomas, and advanced adenomas. In addition, the APCS-SDC2 scoring system significantly increased the specificity for advanced adenomas, and the sensitivity was not significantly different from that of the APCS scoring system and was consistent with colonoscopic results combined with pathological detection.
Limitations
This study has some limitations. Screening cost is a factor that must be considered in screening strategies. The trade-off between the cost of fecal SDC2 methylation testing and patient willingness to accept invasive examinations is key to determining whether this technology has economic benefits.36 Economic benefit analysis was not included in this study.
Conclusions
Among individuals with positive fecal SDC2 methylation test results, the detection rates of advanced adenomas were significantly elevated, and colonoscopy should be prioritized. The APCS-SDC2 scoring system, which integrates fecal SDC2 methylation testing, demonstrated superior risk stratification performance for advanced adenomas compared with the APCS scoring system, along with higher specificity.
Declarations
Acknowledgement
The authors gratefully acknowledge Hangzhou AI WEI KE BIOTECH Co., Ltd. for providing fecal sampling kits, sample preservation solution, and human SDC2 gene methylation detection kits.
Ethical statement
This study adhered to the Declaration of Helsinki (as revised in 2024) and was approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang Chinese Medical University (approval number: 2023-KLS-128-02). Written informed consent was obtained from all participants.
Data sharing statement
The datasets analyzed during this study are available from the corresponding author upon reasonable request.
Funding
This study received no funding support.
Conflict of interest
Prof. Bin Lyu has been an editorial board member of Cancer Screening and Prevention since February 2022. The authors have no other conflicts of interest related to this publication.
Authors’ contributions
Writing - original draft, data curation, formal analysis, methodology, visualization (XJ), validation (XJ, JZ, YC, LX, MC, TY, HJ, HB), conceptualization (XJ, JZ, BL), project administration (JZ), investigation (YC, LX, MC, TY, HJ, HB, LH, YH), writing - review & editing, supervision, and funding acquisition (BL). All authors have approved the final version and publication of the manuscript.