Independent risk factors and a predictive model for surgical site infection following colorectal cancer surgery

Abstract

BACKGROUND

Colorectal cancer (CRC) ranks third in global cancer incidence and second in cancer-related mortality, with surgical resection remaining the cornerstone of curative treatment for localized and advanced disease. Although minimally invasive approaches such as laparoscopy have reduced surgical trauma and accelerated recovery, postoperative complications-particularly surgical site infection (SSI)-remain prevalent due to the anatomical complexity of colorectal surgery, high intraluminal bacterial load, and frequent patient comorbidities including advanced age and malnutrition. SSI delays wound healing, prolongs hospitalization, increases healthcare costs, and may postpone adjuvant therapy, ultimately compromising long-term prognosis. Reported SSI rates vary widely across studies, reflecting differences in surgical techniques, perioperative management, and diagnostic criteria. While multiple factors-such as age, obesity, diabetes, and surgical approach-have been proposed as potential risk contributors, their independent associations and relative weights remain controversial, especially regarding the effect of open vs laparoscopic surgery. Clarifying these independent risk factors is critical for targeted prevention and individualized perioperative management in CRC patients.

AIM

To investigate the incidence of postoperative SSI and associated risk factors in CRC patients.

METHODS

Clinical data were retrospectively collected and analyzed from 228 patients who underwent CRC surgery at the Second Affiliated Hospital of University of South China between January 2021 and May 2025. The incidence of postoperative SSI was calculated. Univariate and multivariate logistic regression analyses were performed to identify risk factors for SSI after CRC surgery. A combined prediction model was constructed, and the predictive performance of individual factors and the model was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

Among the 228 patients, 45 developed postoperative SSI, yielding an overall infection rate of 19.74% (45/228). Among 104 patients who underwent laparoscopic surgery, 11 developed infection, corresponding to an infection rate of 10.58% (11/104); among 124 patients who underwent open surgery, 34 developed infections, corresponding to an infection rate of 27.42% (34/124). Overall, 48 pathogenic strains were isolated from the 45 patients with SSI, including 27 gram-negative bacterial strain (56.25%), 17 gram-positive bacterial strains (35.42%), and four fungal strains (8.33%). Logistic regression analysis identified surgical approach [odds ratio (OR): 16.687, 95%CI: 6.118-45.514], age (OR: 1.071, 95%CI: 1.018-1.126), obesity (OR: 13.895, 95%CI: 2.826-68.320), and incision length (OR: 1.384, 95%CI: 1.183-1.619) as independent risk factors for postoperative SSI in patients with CRC (all SSIs P < 0.05). On ROC curve analysis, the combined prediction model based on these independent risk factors demonstrated high predictive performance (area under the curve = 0.898).

CONCLUSION

Open surgery, advanced age, obesity, and longer incision length were independent risk factors for postoperative SSI in CRC. The combined prediction model based on these factors showed high discriminative value and may help clinicians identify high-risk patients.

Key Words: Colorectal cancer; Postoperative incisional infection; Laparoscopic surgery; Open surgery; Independent risk factors

Core Tip: This retrospective study of 228 patients who underwent colorectal cancer surgery found a postoperative surgical site infection rate of 19.74%, with a lower rate after laparoscopic surgery. Open surgery, advanced age, obesity, and longer incision length emerged as independent risk factors. A prediction model combining these factors showed high discriminatory value (area under the curve = 0.898) for identifying high-risk patients.

INTRODUCTION

Colorectal cancer (CRC) is a common digestive tract malignancy worldwide, ranking third in incidence and second in cancer-related mortality[1]. Surgical resection remains the main curative treatment for localized and advanced CRC[2]. With advances in medical technology, minimally invasive approaches, such as laparoscopy have become increasingly prevalent, effectively reducing surgical trauma and accelerating postoperative recovery recovery[3].

However, because of the anatomical location, complexity and duration of the surgical procedure, and frequent comorbidities, such as advanced age and poor nutritional status, postoperative complications after radical CRC surgery remain common[4,5]. Among these complications, surgical site infection (SSI) is one of the most frequent and poses a major threat to postoperative recovery[5,6]. SSIs can trigger delayed wound healing, dehiscence, and even deep-seated infection, prolonging hospital stay, increasing the healthcare burden, and potentially delaying subsequent adjuvant therapy, thereby affecting long-term prognosis[7]. Because colorectal contents carry a high bacterial load and intraoperative contamination may occur, the incidence of SSI after colorectal surgery is significantly higher than that after clean surgery[8]. Variations in reported infection rates across studies may be attributed to differences in study populations, surgical techniques, perioperative management, and diagnostic criteria[9]. Therefore, identifying independent risk factors for postoperative SSI in patients with CRC is clinically important for targeted prevention and optimized perioperative management. Existing research suggests that infection risk is associated with patient-specific conditions (e.g., age, nutritional status, and comorbidities), disease characteristics, and surgery-related factors (e.g., surgical approach and duration)[10,11]. However, the strength and independence of these associations remain debated, particularly for the effect of surgical approach (open vs laparoscopic) on infection risk, which requires further clinical evidence.

Therefore, this study retrospectively analyzed clinical data from patients who underwent CRC surgery to determine the incidence of postoperative SSI and identify associated risk factors, with the aim of supporting clinical identification of high-risk patients and individualized prevention and control strategies.

MATERIALS AND METHODS

Data source

This study retrospectively analyzed clinical data from 250 patients who underwent CRC surgery at the Second Affiliated Hospital of University of South China from January 2021 to May 2025.

Inclusion criteria: (1) Patients meeting the diagnostic criteria for CRC[12], as confirmed by pathological examination of endoscopic biopsy specimens; (2) Patients with surgical indications who underwent surgical treatment; (3) Patients with clear consciousness and good mental status; and (4) Patients with complete clinical data.

Exclusion criteria: (1) Patients who received non-surgical treatment; (2) Those with cardiovascular or cerebrovascular disease, or autoimmune disease; (3) Those with severe liver or kidney dysfunction or mental disorders; (4) Those with other colorectal tumors, such as stromal tumors or melanoma, or multiple organ malignancies with metastases, such as peritoneal or lung metastasis; (5) Those with contamination in the surgical area; (6) Those with pre-existing infectious disease before surgery; and (7) Pregnant or lactating women, were excluded. Ultimately, 228 patients were included in the analysis.

This study was approved by the ethics committee of the Second Affiliated Hospital of University of South China.

Study design

Clinical data for the enrolled patients were retrospectively reviewed from inpatient medical records. Potential infection-associated factors were assessed, including sex, age, body mass index (BMI), Duke stage, surgical approach (laparoscopic/open surgery), incision length, and presence of diabetes mellitus (DM). Pathogen detection results for SSIs after CRC surgery were also analyzed.

Perioperative antibiotic prophylaxis

All patients received standardized antibiotic prophylaxis. Cefoxitin (2 g) was administered intravenously 30-60 minutes before skin incision; a 3-g dose was used for patients weighing > 80 kg. For patients with β-lactam allergy, metronidazole (500 mg) plus gentamicin (1.5 mg/kg) was administered. Routine postoperative antibiotic prophylaxis was not given.

Wound protectors (Alexis^® O-ring retractor) were routinely used in all open surgeries. Specimen retrieval bags were used in laparoscopic surgeries. No other infection-prevention devices (e.g., topical antibiotics or negative-pressure dressings) were applied.

Outcome measures

Primary outcome measures: (1) SSI: The incidence of SSI in the enrolled patients was analyzed, and the overall infection rate and subgroup infection rates by surgical approach (laparoscopic/open surgery) were calculated. The formula was as follows: (Number of infection cases/total number of corresponding cases) × 100%. Surgical incision infection was diagnosed according to the following criteria[13]: (a) Redness and swelling of the surgical incision with visible purulent secretion; (b) Local pain upon incision compression and purulent secretion from a dehisced incision; (c) Pus observed during deep puncture or drainage of the incision; and (d) A positive result from etiological testing. Diagnosis was confirmed if any one of these criteria was met; and (2) Distribution of pathogenic bacteria: Pathogen culture and identification results from secretion or tissue samples from patients with incision infections were analyzed. The total number of isolated pathogen strains was recorded, and pathogens were classified as gram-negative bacteria, gram-positive bacteria, or fungi. The constituent ratio of each category was calculated. For patients with deep incision infections, pus was collected using a sterile syringe; for patients with superficial incision infections, purulent secretions were collected using a broth swab. All specimens were submitted for testing. Pathogens were identified using the EXS 3000 fully automated microbial mass spectrometry system (Chongqing Zybio Co., Ltd., China). Quality control strains (National Institute for the Control of Pharmaceutical and Biological Products, Ministry of Health) included Staphylococcus aureus ATCC25923, Escherichia coli ATCC25922, and Pseudomonas aeruginosa ATCC27853.

Secondary outcome measures: (1) Baseline and perioperative indices of patients. Infection-associated factors were analyzed, including demographic characteristics (age, sex, BMI), surgical approach, DM, incision length, and Duke stage; (2) Analysis of independent risk factors: Multivariate logistic regression was performed to identify risk factors for SSI in patients with CRC; and (3) Predictive efficacy of risk factors: A combined prediction model was constructed using the independent risk factors identified in multivariate analysis. The area under the receiver (AUC), operating characteristic curve (ROC) was used to evaluate the model’s discriminatory ability for predicting SSI.

Duke staging definition

Duke stage C was defined as tumor penetration of the muscularis propria with regional lymph node metastasis; stage D was defined as distant metastasis (liver, lung, or peritoneum). Staging was based on postoperative pathological examination.

Statistical analyses

Statistical analyses were performed using SPSS 20.0 (IBM Corp., Armonk, NY, United States), and graphs were generated using GraphPad Prism 7 (GraphPad Software Inc., San Diego, CA, United States). Normally distributed measurement data were expressed as mean ± SD and compared using the independent-samples t-test. Count data were expressed as n (%) and compared using the χ² test. Univariate and multivariate logistic regression analyses were performed to identify risk factors for SSI in patients with CRC. ROC curves were used to evaluate the predictive efficacy of these risk factors. P < 0.05 was considered statistically significant.

RESULTS

Incision infection in postoperative CRC patients

Among the 228 enrolled patients, 45 developed SSIs, resulting in an overall infection rate of 19.74% (45/228) (Table 1). Of whom, 104 patients underwent laparoscopic surgery, with 11 cases of infection, yielding an infection rate of 10.58% (11/104); 124 patients underwent open surgery, with 34 cases of infection, yielding an infection rate of 27.42% (34/124, P = 0.002).

Table 1 Comparison of surgical site infection rates by surgical approach.

Surgical approach	Total cases	Infection cases	Infection rate (%)	P value
Laparoscopic	104	11	10.58	0.002
Open	124	34	27.42
Total	228	45	19.74

Distribution of pathogens in SSIs in CRC patients

A total of 48 pathogen strains were isolated from the 45 patients with incision infections (Table 2). Of these, 27 strains were Gram-negative bacteria (56.25%), 17 were Gram-positive bacteria (35.42%), and four were fungi (8.33%).

Table 2 Distribution of pathogens in surgical site infections in colorectal cancer patients.

Pathogen category	Number of strains (n)	Composition ratio (%)
Gram-negative bacteria	27	56.25
Gram-positive bacteria	17	35.42
Fungi	4	8.33
Total	48	100

Comparison of general data between the infection and non-infection group

Patients were assigned to an infection (n = 45) or a non-infection (n = 183) group based on SSI status. The infection group had significantly higher age (66.55 ± 8.51 years), BMI (25.90 ± 3.03 kg/m²), and incision length (12.26 ± 3.31 cm) than the non-infection group (61.73 ± 9.03 years, 22.01 ± 2.97 kg/m², and 9.89 ± 2.86 cm, respectively; all P < 0.05) (Table 3). Regarding comorbidities, the infection group had a significantly higher proportion of patients with DM than the non-infection group [48.89% (22/45) vs 13.66% (25/183), P < 0.05]. The infection group also had a significantly higher proportion of patients who underwent open surgery than the non-infection group [75.56% (34/45) vs 49.18% (90/183), P = 0.002]. However, sex composition and Duke stage distribution (stage C/D) did not differ significantly between groups (both P > 0.05).

Table 3 Comparison of general data between the infection and non-infection groups, n (%)/mean ± SD.

	Infection group (n = 45)	Non-infection group (n = 183)	χ2/t	P value
Age (years)	66.55 ± 8.51	61.73 ± 9.03	3.271	0.001
Sex			0.061	0.805
Male	19 (42.22)	81 (44.26)
Female	26 (57.78)	102 (55.74)
BMI (kg/m2)	25.90 ± 3.03	22.01 ± 2.97	7.858	< 0.001
Surgical approach
Open surgery	34 (75.56)	90 (49.18)	10.131	0.002
Laparoscopic surgery	11 (24.44)	93 (50.82)
Comorbid diabetes mellitus			27.391	< 0.001
Yes	22 (48.89)	25 (13.66)
No	23 (51.11)	158 (86.34)
Incision length (cm)	12.26 ± 3.31	9.89 ± 2.86	4.828	< 0.001
Duke stage (stage C/D)			0.349	0.555
Stage C	28 (62.22)	105 (57.38)
Stage D	17 (37.78)	78 (42.62)

Measurement data (age, body mass index, incision length) were compared using independent samples t-test; counting data (sex, surgical approach, diabetes mellitus, duke stage) were compared using χ² test. BMI: Body mass index.

Analysis of risk factors for SSI in patients with CRC

Variables with notable differences in the univariate analysis were assigned values (Table 4) and included in multivariate analysis. Logistic regression analysis identified surgical approach [odds ratio (OR): 16.687, 95%CI: 6.118-45.51], age (OR: 1.071, 95%CI: 1.018-1.126), obesity (OR: 13.895, 95%CI: 2.826-68.320), and incision length (OR: 1.384, 95%CI: 1.183-1.619) as independent risk factors for SSI in patients with CRC (all P < 0.05) (Table 5).

Table 4 Assignment.

Factors	Assignment
	0	1
Surgical methods	Laparoscopic surgery	Open surgery
Diabetes mellitus	No	Yes
Infection	No	Yes
Obesity (BMI ≥ 28 kg/m2)	No	Yes

BMI: Body mass index.

Table 5 Multivariate logistic regression analysis of surgical site infection in colorectal cancer patients.

Factors	B	SE	Wals	df	Sig.	Exp (B)	95%CI for EXP(B)
							Lower limit	Upper limit
Surgical methods	2.815	0.512	30.226	1	0.000	16.687	6.118	45.514
Diabetes mellitus	0.774	0.477	2.634	1	0.105	2.168	0.851	5.521
Age	0.068	0.026	7.070	1	0.008	1.071	1.018	1.126
Obesity	2.632	0.813	10.488	1	< 0.001	13.895	2.826	68.320
Incision length	0.325	0.080	16.432	1	< 0.001	1.384	1.183	1.619

Predictive efficacy of risk factors and the combined model

To evaluate the discriminative ability of the individual independent risk factors and the combined prediction model, ROC curves were plotted and relevant indicators were calculated (Figure 1 and Table 6). The combined prediction model, which included surgical approach, age, obesity, and incision length, demonstrated the highest predictive performance, with an AUC of 0.898, sensitivity of 77.05%, specificity of 88.89%, and an overall accuracy of 79.39%.

Figure 1  Receiver operating characteristic curves of the predictive efficacy of risk factors and the combined model.

Table 6 Predictive efficacy of individual predictors and the combined model for surgical site infection.

Predictors	Area under the curve	Sensitivity (%)	Specificity (%)	Accuracy (%)
Joint	0.898	77.05	88.89	79.39
Obesity	0.600	97.81	22.22	82.90
Surgical approach	0.772	72.13	82.22	74.12
Incision length	0.704	61.20	73.33	63.6
Age	0.647	53.01	73.33	57.02

Construction and validation of the nomogram

A nomogram for predicting the risk of SSI in patients with CRC was constructed based on the four independent risk factors identified by multivariate logistic regression analysis: Surgical approach, age, obesity, and incision length (Figure 2).

Figure 2  Nomogram for predicting the risk of surgical site infection in patients with colorectal cancer.

DISCUSSION

Although radical surgery can control CRC progression, it is prone to SSI, which can substantially compromise patient prognosis[14,15]. This study retrospectively analyzed 228 patients to investigate the incidence, etiological characteristics, and related risk factors of SSIs and to construct a combined assessment model.

The overall incision infection rate in this study was 19.74%, which was slightly lower than the range reported in recent literature. For instance, a systematic review by Cai et al[16] reported an incidence of 23% to 26%. This difference may reflect variations in study population characteristics, perioperative management strategies, or subtle differences in diagnostic criteria for infection. Furthermore, the SSI rate was 10.58% after laparoscopic surgery, significantly lower than the 27.42% observed after open surgery. This finding suggests that minimally invasive surgery may reduce the risk of incision infection, and surgical approach was also independently associated with infection risk. Similarly, Yamamoto et al[17] identified open surgery as an independent risk factor for incision infection. Compared with laparoscopic surgery, open surgery may cause greater tissue trauma and a stronger inflammatory response. A larger incision directly increases tissue exposure to a contaminated environment and may also increase the likelihood of subcutaneous fat liquefaction and dead-space formation, creating conditions for pathogen colonization[18,19]. Moreover, open surgery may induce more severe systemic stress and immunosuppression, further weakening local and systemic anti-infection defences[20]. The OR for open surgery in our study (OR = 16.687) was higher than that reported in most previous studies, in which the OR generally ranges from 2 to 5. This may be explained by its strong correlation with longer incisions, a high obesity rate, and the limited sample size (n = 45 events), which may have widened the confidence interval and produced a more extreme estimate. Regarding etiological distribution, the pathogens causing incision infections were predominantly gram-negative bacteria, followed by gram-positive bacteria and fungi. This distribution is consistent with the common pathogen spectrum of abdominal surgical incision infections[21]. Because the colorectal lumen contains complex flora, mainly Escherichia coli[22], enterogenous contamination is difficult to avoid completely during surgery, providing an anatomical basis for the high detection rate of gram-negative bacteria. Fungal infections may be associated with preoperative patient condition, broad-spectrum antibiotic use, and immunosuppression[23].

Further univariate and multivariate logistic regression analyses identified surgical approach, age, obesity, and incision length as independent risk factors for SSI. Among these, surgical approach showed the strongest risk association. Previous studies have confirmed the advantages of laparoscopic surgery in reducing postoperative pain, accelerating recovery, and shortening hospital stay[24,25]. However, its effect on specific infectious complications and the magnitude of this effect have varied across studies. After adjustment for confounding factors in multivariate analysis, this study confirmed laparoscopic surgery as an independent protective factor against incision infection. The underlying mechanisms may be multifactorial: First, laparoscopy is performed through several small incisions, thereby minimizing trauma to the abdominal wall soft tissues, vascular disruption, and the surface area exposed to airborne pathogens; these effects reduce the physical basis for incision infection[26]. Second, compared with open surgery, laparoscopic surgery has a smaller effect on systemic inflammation and immunosuppression, which may help maintain stronger local and systemic anti-infective defenses[27]. Third, the high-definition magnified field of view may support more precise dissection and better preservation of blood supply, reducing tissue ischemia and necrosis, which can trigger infection[28]. Age and obesity are widely recognized baseline patient-related risk factors. For instance, Panos et al[29] confirmed that advanced age and higher BMI, particularly BMI ≥ 30 kg/m², are significant independent risk factors for SSI in CRC. Furthermore, a recent systematic review and meta-analysis of 29 studies[30] showed that obesity (BMI ≥ 30 kg/m²) significantly increased the overall risk of incision infection (OR: 1.49, 95%CI: 1.37-1.70), supporting the association between BMI and infection risk. Incision length, a direct quantitative indicator of surgical trauma, was also an independent risk factor in this study. This finding is consistent with the result for surgical approach and further supports the principle that reducing tissue trauma is central to infection prevention.

Furthermore, this study constructed a combined prediction model based on the four independent risk factors. The model showed favorable predictive performance, with an AUC of 0.898, a sensitivity of 77.05%, a specificity of 88.89%, and an overall accuracy of 79.39%. These results indicate that the model has strong discriminative ability. This study also developed a nomogram to visualize the regression model for predicting SSI risk in patients with CRC. Internal validation showed good model calibration. This tool is easy to use and may facilitate individualized clinical risk assessment.

However, this study has some limitations. First, the single-center retrospective design and relatively limited sample size may have introduced selection bias. Second, the risk factors were primarily extracted from medical records; therefore, some potential factors that were not routinely recorded or were difficult to quantify could not be included, which may have influenced the results. Third, although the prediction model performed well in this cohort, its external validity requires prospective multicenter validation across regions and healthcare institutions of different sizes to confirm its general applicability and stability. Additionally, the exact timing of infection diagnosis was not systematically recorded, which precluded analysis of the median time to infection onset.

CONCLUSION

Open surgery, advanced age, obesity, and longer incision length were independent risk factors for postoperative SSI in CRC. The combined prediction model based on these factors showed high discriminative value and may help clinicians identify high-risk patients.