Novel approach to risk stratification: Integrating waist-hip ratio for predicting advanced colorectal neoplasia

Abstract

The urgent necessity for enhanced risk stratification to improve the efficiency of colonoscopy screening is underscored by the fact that colorectal cancer (CRC) continues to be a primary cause of global cancer mortality. Conventional models mostly rely on generalized obesity markers including body mass index (BMI), which does not effectively represent oncogenic risk linked with abdominal obesity. Liu et al undertook a large-scale case-control study comprising 6484 first-time colonoscopy patients at a prominent Chinese hospital between 2020 and 2023 to overcome this restriction. Age, male sex, smoking status, and raised waist-hip ratio (WHR) were found by multivariate logistic regression as independent predictors of advanced colorectal neoplasia (ACN). In a validation cohort of 1891 individuals, a new 7-point risk scoring model was created and stratified into low- (5.0%) ACN prevalence, moderate- (10.3%) and high-risk (17.6%). With C-statistic = 0.66 the model showed better discriminating ability than the Asia-Pacific Colorectal Screening (APCS) score (C-statistic = 0.63) and the BMI-modified APCS model. These results fit newly published data showing central obesity as a major carcinogenic driver via pro-inflammatory visceral adipokine channels. With the use of WHR, patient risk classification is greatly improved, providing a practical tool to make the most of screening resources in the face of rising CRC incidence rates. Finally, multi-ethnic validation is necessary for the WHR-based scoring model to be considered for integration into global CRC preventive frameworks, since it improves the accuracy of ACN risk prediction.

Key Words: Colorectal cancer; Advanced colorectal neoplasia; Risk prediction model; Waist-hip ratio; Central obesity; Colonoscopy screening; Cancer risk stratification; Visceral adiposity; Predictive analytics; Precision oncology

Core Tip: This work presents a novel approach to estimate the risk of advanced colorectal neoplasia by means of waist-hip ratio (WHR), an indicator of abdominal obesity. Although traditional models largely rely on body mass index (BMI), BMI does not entirely depict the risk resulting from fat around the waist. A new scoring method was made in this study by using WHR along with age, gender, and smoking habits. To save time, money, and lives, WHR can improve the efficacy of colonoscopy screening and assist doctors identify high-risk patients earlier.

INTRODUCTION

Colorectal cancer (CRC) is one of the most significant global health concerns of the 21^st century, as it is the third most frequently diagnosed cancer and the second most prevalent cause of cancer related deaths worldwide[1]. China, where an anticipated 550000 new CRC cases and 290000 related deaths were documented in 2020 alone, bears especially heavy burden[2]. These numbers highlight the critical need of efficient early detection techniques, especially aimed at advanced colorectal neoplasia (ACN), which consists of advanced adenomas and early-stage carcinomas that usually develop to full blown CRC. To detect and remove these precancerous lesions, colonoscopy is still considered the most effective method[3]. Although it has been demonstrated to lower CRC incidence by 53% to 72%, it is difficult to apply widely because to its invasiveness, high expense, and restricted accessibility. This is particularly true in areas with limited resources. This reality has motivated researchers to investigate more sophisticated, cost-effective, and readily available risk stratification methods that can assist in the prioritisation of high-risk individuals for colonoscopy screening and the reduction of unnecessary procedures among low-risk populations[4]. In a recent study Liu et al[5] proposes a new risk prediction model including waist-hip ratio (WHR), an emerging and more accurate biomarker of central obesity, therefore addressing this urgent need. The authors started research to improve current risk scoring systems after realising the growing evidence that colorectal carcinogenesis is more closely correlated with abdominal obesity rather than generalised obesity indicated by body mass index (BMI).

A recent large-scale study by the American Medical Association, encompassing over 500000 individuals, found that waist circumference and waist-to-hip ratio (WHR) are stronger predictors of CRC than BMI. In particular, people in the highest WHR quartile had a 40% higher chance of getting CRC, and people with the largest waist circumference had a 37% higher risk, compared to people in the lowest quartile. The population-attributable risks were 17.6% and 17.3%, which are both much higher than the 9.9% linked to BMI. These results support the growing belief that central obesity, especially WHR, is a better and more clinically useful way to predict the risk of CRC[6]. From July 2020 through December 2023, 6483 Chinese patients visiting the University of Hong Kong-Shenzhen Hospital for their initial colonoscopy were enrolled in their study. Out of this pool, 1891 patients made the validation cohort, and 4592 patients made the derivation cohort utilised to create the scoring model. To maintain the integrity of the sample population, the study painstakingly eliminated those with past colorectal surgery, inflammatory bowel illness, incomplete colonoscopy, and poor bowel preparation[7]. The four main independent predictors of ACN by means of multivariate logistic regression analysis: Rising age, male gender, smoking, and higher WHR. Importantly, WHR was better at capturing the role of central obesity in colorectal carcinogenesis than BMI, which was used extensively in earlier models like the Asia-Pacific Colorectal Screening (APCS) and its BMI modified version[8]. This was evident in the multivariate model, where BMI was not a significant predictor. This study constructed on these findings a useful 7-point risk grading system. Male gender, smoking, and high WHR each earned one point; age added up to four points depending on the age bracket; those 70 years of age and above scored the highest overall. Based on their overall score, patients were then categorised as low risk (0-2 points), moderate risk (3-4 points), and high risk (5-7 points). Within the derivation cohort, ACN prevalence ranged from 3.3% for the low-risk group to 9.3% for the moderate risk to 18.5% for the high risk. The validation cohort reflected these results: ACN prevalence in the corresponding groups was 5.0%, 10.3%, and 17.6%. Measuring the model's discriminating ability with the C-statistic, it came out ahead of both the BMI-modified version (0.62) and the conventional APCS model (0.63). With a Hosmer-Lemeshow goodness-of-fit P-value of 0.71, which shows a strong agreement between expected and observed outcomes.

While WHR is a simple and useful tool, it does have some limitations. Measurements can vary due to differences in technique or how the tape is placed, which may affect accuracy. Results can also differ between observers, and WHR may not work equally well across all ethnic groups due to variations in body fat distribution. These factors highlight the need for careful standardization and broader validation in diverse populations[9]. The inclusion of WHR into risk analysis is a major change in our method of CRC risk assessment. WHR offers a straightforward yet clinically strong surrogate for visceral adiposity the kind of fat most linked with metabolic abnormalities and oncogenesis unlike BMI, which fails to identify fat distribution or separate between fat and muscle mass. Promoting tumour formation and progression, visceral adipose tissue secretes several pro-inflammatory cytokines and adipokines, including interleukin-6, tumour necrosis factor-alpha, and Leptin. WHR thus not only improves the model statistically but also helps it more precisely to match the fundamental pathophysiological processes of CRC formation. WHR measurement is cheap, non-invasive, and readily used in clinical practice, which makes it the perfect variable for large-scale screening initiatives especially in environments where access to complex diagnostics is difficult. Given current CRC screening technology, our WHR-based model presents a particularly sensible approach. Although non-invasive screening procedures such faecal immunochemical assays, stool DNA testing, and new liquid biopsy approaches are used increasingly, their main purposes are detection rather than risk stratification[10]. By contrast, WHR is meant to identify who should get screened, thereby acting as a useful upstream filter to better allocate resources. Furthermore, unlike models mostly dependent on family history a variable proven unreliable in this study due to limited historical data in the Chinese population. This model depends on measurable, modifiable, and easily obtained clinical parameters. This improves its accuracy and relevance especially in populations where family history is sometimes absent or under recorded. This study has overall produced a strong, evidence-based improvement in the field of CRC risk assessment. Their WHR inclusive model not only exceeds current APCS based models in predicting accuracy but also in clinical feasibility and biological relevance. Such developments are not only good but also necessary as CRC incidence rises and Healthcare systems try to strike a mix between practical delivery and precision medicine. This model establishes a new benchmark for risk prediction in colorectal screening and calls for more research on many populations to validate its global relevance[11]. While the WHR-based model provides a practical and readily available response, it is critical to contextualize it within the larger progression of CRC risk assessment tools. Recent improvements in artificial intelligence have made it possible to create models that use electronic health records and imaging data to make predictions for each person. Furthermore, polygenic risk scores, which aggregate genetic variations associated with CRC, are being investigated for individualized screening. Hybrid models that combine WHR with fecal immunochemical testing are also looking well because they use both morphological and biochemical markers. WHR stands out from these complicated methods because it is inexpensive and simple to use, especially in primary care and low-resource settings.

Socio-economic benefits

For CRC screening, the implementation of a risk assessment model based on WHR offers significant socio-economic benefits. Healthcare systems can prioritise high-risk patients for colonoscopy by stratifying people based on their actual risk of ACN, therefore lowering needless operations and related expenses for low-risk groups. For public health systems particularly in areas with insufficient or overstretched medical infrastructure, this focused deployment of resources results in notable financial savings. The approach is perfect for large-scale use in both urban and rural environments, including underprivileged people sometimes excluded from comprehensive screening programs, since it depends on WHR: A simple, non-invasive, low-cost test. Apart from direct medical savings, the larger influence on society is as crucial. Early identification of ACN greatly lessens the burden of advanced CRC, hence lowering treatment costs, hospitalizations, and survival rates. This helps people to keep their output and lowers long-term economic costs connected with incapacity or early death[12].

Clinical implications

In the context of precision medicine and population-level cancer prevention, the integration of a WHR-based risk stratification model into CRC screening approach has a substantial clinical impact. The model provides an evidence-based, biologically relevant method to identify persons at increased risk for ACN by including WHR as a known surrogate marker of visceral adiposity along with age, sex, and smoking history. WHR more precisely measures central adiposity, which has been technically related by pro-inflammatory adipokine signalling, insulin resistance, and chronic low-grade inflammation to colorectal carcinogenesis than BMI[13]. This raises the prediction accuracy and pathophysiological validity of the model. Important in both high-demand urban locations and underfunded Healthcare systems, this focused strategy lowers procedure burden, minimises patient exposure to needless interventions, and maximises endoscopic resource use. Moreover, WHR is a low-cost, non-invasive measurement that may be readily included into daily outpatient procedures, therefore facilitating early risk assessment at the primary care level. Therefore, the model enhances its capacity to improved early detection rates, streamline patient triage, and support evidence-based resource allocation by bridging the gap between observational analysis and practical application.

CONCLUSION

A significant step forward in the prevention of CRC has been made with the incorporation of WHR into risk prediction models. This model improves our capacity to find those really at high risk by changing the emphasis from general obesity measures such as BMI to a more physiologically and epidemiologically relevant predictor of visceral adiposity. While staying simple, affordable, and scalable appropriate for implementation across a spectrum of healthcare systems, including those with low resources, it achieves better prediction accuracy than current frameworks. Beyond predicting accuracy this approach provides real advantages like better colonoscopy resource allocation, less procedure load on low-risk people, and more screening accessibility for underprivileged groups, WHR-based model captures that idea brilliantly. Clinical practice and national screening recommendations should embrace risk-adapted strategies based on both scientific rigour and practical viability. This will help us to go towards fair, effective, and life-saving CRC prevention. To make sure that this model can be used with a wide range of individuals, future study should focus on testing it with a variety of multi-ethnic and multi-center groups. Furthermore, engagement with public health officials and clinical organisations is required to investigate integration paths into national CRC screening programmes and clinical guidelines. This could help with early detection efforts and make the most use of resources in different Healthcare settings.