Improvement of Asia-Pacific colorectal screening score and evaluation of its use combined with fecal immunochemical test

Colorectal cancer (CRC) is the fourth leading malignant tumor for incidence and the second most common for mortality in both sexes across the world based on the 2018 GLOBOCAN estimates [1], and the morbidity of CRC in the Chinese population has continued to rise in recent years [2]. CRC screening, including the fecal occult blood test (FOBT) and colonoscopy, has been shown to effectively reduce the prevalence of colorectal neoplasia and increase survival [3‐5]. Guidelines generally recommend that CRC screening should be carried out in people aged over 50 years via FOBT, including guaiac­based (gFIT) and immunochemical (FIT), or endoscopy, including colonoscopy and sigmoidoscopy [6], which is hindered to some extent in China due to the large population and limited medical resources. It is reported that the FIT is relatively cost-effective and annual FIT can reduce CRC mortality by approximately 30% [7, 8], but the effect is achieved in prerequisite that positive FIT be followed by more expensive tests, including colonoscopy. Therefore, it is important to develop a simple predictive model that can be used to screen high-risk (HR) groups of CRCs to make subsequent screening methods, mainly colonoscopy, more effective and targeted. Moreover, due to the cost-effectiveness of FIT, the risk score can be combined with FIT to achieve a higher level of screening efficiency.

The Asia-Pacific Colorectal Screening (APCS) score was established via the study of a derivation set of 860 subjects and a validation set of 1892 subjects [9]. Nevertheless, the original APCS model is relatively simple and is based merely on elementary clinical data, including sex, age, family history and smoking status. Other risk factors, such as diabetes mellitus [10], alcohol consumption [11] and obesity [12], were overlooked, although they have been reported to be closely related to CRC in previous studies. In addition, the original APCS score overlooked the significance of FIT in current CRC screening and failed to test the combination of the score with FIT. Therefore, our team hoped to further improve the original APCS score model by adding other risk factors to make it more comprehensive and effective and investigate the validity of the combined use of the modified score and FIT.

Based on a list of CRC-related risk factors, including sex, age, smoking status, alcohol consumption, diabetes, family history, obesity, diet and exercise, this study aimed to improve the existing APCS score and validate the modified model to confirm its effectiveness in screening high-risk groups of CRC among a Chinese asymptomatic population and further test the validity of the score combined with FIT.

Effective screening methods, principally referring to FIT and colonoscopy, can reduce the prevalence and mortality of CRCs. However, standardized and effective CRC screening strategies cannot be carried out across China, mainly due to resource limitations and lack of health awareness, leading to the urgency for more efficient and targeted primary screening schedules. Under such conditions, the economical and simple risk score system or its combined use with FIT are attracting an increasing level of interest in the world. Some studies [17‐19] have attempted to establish a screening questionnaire model for a high-risk group of CRCs that is generally not comprehensive and short of feasibility. The APCS system established by scholars from the Chinese University of Hong Kong [9] considered risk factors including sex, age, family history and smoking status and has been validated by different studies in various parts of Asia-Pacific area and even in Western countries [20‐28]. However, the APCS score failed to collect information on the height and weight of participants, so it was impossible to judge the role of BMI in the prediction system. In addition, the original score failed to take FIT, which is also cost-effective and validated in current CRC screening guidelines, into account.

In our study, risk factors related to colorectal neoplasia were extensively reviewed and evaluated to establish a modified screening model for CRC. The prevalence of ACN in the derivation set and the validation set were 4.1 and 3.7%, respectively, which were generally consistent with previous findings [9, 13‐15, 28]. In previous research, the contributions of age, gender, smoking, drinking, family history, diabetes, diet and exercise [10, 17‐19, 29‐32] have been recognized as major risk factors for CRC. Based on data analysis in this study, the final risk score incorporated age, family history, smoking, alcohol consumption, diabetes and BMI as factors (Table 3). According to this modified score, the HR cohort in the validation set exhibited a 3.4-fold (95% CI 1.8–6.4) increased risk than the AR cohort for ACN. The C-statistic for the modified risk score was 0.69 ± 0.04, slightly higher than that for the original APCS system. Overall, the modified APCS score showed good discrimination and screening effect through data validation. Notably, our modified score assigned a factor age ≥ 70 with five points, which was higher than the original APCS score, which assigned an age of 50–69 with two points and an age of ≥70 with three points, and our study defined two tiers of risk instead of the three in the original score. The weight of factors came from the univariate and multivariate data analysis of our study, and the cut-off value of the two risk tiers was defined via the analysis of the ROC curve in convenience of developing a practical CRC screening strategy in China. Our modified score recommends that an asymptomatic subject is categorized as a high-risk tier for CRC if he is ≥70 years old or has one of these factors, including 59–69 years old, a CRC family history and a past history of diabetes mellitus with any other risk factors, or is overweight with a habit of smoking and drinking. Overall, the modified score is more efficient and simpler than the original score. For example, based on the original score, a patient ≥70 years of age is assigned 3 points and defined as moderate risk (2–3 points), but it is actually difficult to decide for this individual whether to undergo further screening. In contrast, the two tiers of risk avoid such embarrassment in regard to practical implementation.

Compared to the original score, we introduced diabetes as a key risk factor with 2 points, alcohol consumption with 1 point and BMI with 1 point. In addition, sex and other targeted risk factors were left out of our modified score because sex showed significance only for colorectal neoplasia but not for ACN, and other factors remained nonsignificant for both. The incorporation of diabetes and alcohol consumption into the score system was in accordance with previous study results [10, 11]. BMI has long been recognized as a risk factor for CRC [12], and current studies suggest that there is a moderate association between general obesity (as determined by BMI) and the incidence and mortality of CRC and colorectal adenoma [33]. Similarly, several studies have recently worked on modifying the APCS score by adding BMI for the prediction of advanced neoplasia and reported satisfying discrimination efficiency outcomes [23, 34, 35]. Therefore, it is reasonable to incorporate BMI into the CRC prediction and screening questionnaire. Of note, a BMI cutoff of≥23 kg/m² was adopted in this study as a risk factor by logistic regression analysis. We suggest this is reasonable because generally Asian population tend to be thinner and current guidelines in China accepted BMI 24.0–27.9 kg/m² as overweight, and some studies even adopted BMI 23.0–27.9 kg/m² as the definition of overweight [36]. Besides, it is reported that for BMI over 25.0 kg/m², mortality increased approximately log-linearly with BMI, and the hazard ratio per 5 kg/m² units higher BMI was 1.39 (1.34–1.44) in east Asia [37].

Sex is another definite risk factor for CRC, but it failed to show a significant difference in our modeling process. It has been reported that men have an increased risk for advanced neoplasia compared with women, and this positive association was significant across all age groups from age 40 to older than 70 years [38], but it was affected by cancer site, diet, and menopausal status [39]. The confounding influence may account for the failure of adding sex into our new score model. Similar situations exist with the association of diet or exercise with ACN. Therefore, it is advisable to detail the questionnaire items and unify the evaluation criteria to further test the relationship of sex, diet, and exercise with the occurrence of ACN.

In recent years, studies have been investigating the combined use of the prediction score with FIT for raising the screening efficiency of the high-risk cohort for ACN. As reported, the combined use of the APCS score and FIT could correctly instruct 70.6% subjects with ACN and 95.1% subjects with CRC for early colonoscopy examination, thus substantially optimizing medical resources [40]. In our study, the sensitivity and NPVs of combining the modified score with FIT for predicting ACN were higher than those of using either alone, and the combination of these two economical and simple tests can detect the majority of ACN cases as well as CRC. Thus, in our conceptual CRC screening algorithm (Fig. 2), the asymptomatic Chinese subjects should first fill out the risk score questionnaire, and those categorized as AR tiers are then referred for FIT. Finally, colonoscopy is highly recommended for those in the HR tier or in the AR tier but with positive FIT. The entire screening path can triage people for colonoscopy in a more effective way than the traditional screening strategy, which reduces the workload and optimizes the medical resources of ACN screening for clinical practitioners and government policymakers, especially in vast developing countries such as China.

Some limitations exist in this study. First, most of the data were collected through questionnaire by means of self-reporting, so it is possible to misestimate some risk factors. For example, for the risk factor for diabetes, patients with self-knowledge of diabetes may be lower than the actual prevalence of diabetes, and the estimate of diet may be quite subjective, resulting in bias. Second, though the whole screening path combing FIT and the screening score showed good discrimination in triaging HR population for ACN, the C-statistic for the modified risk score was only slightly higher than that for the original APCS system, which may be attributed to confounding factors that lowered the efficacy. Except for the targeted risk factors of CRC, we basically did not compare more detailed information, such as cancer site, pathological types, or quantity of alcohol intake or collected other population characteristics such as menopause status in women and cholecystectomy history. Third, the participants in the derivation and validation cohorts mainly came from hospitals in Beijing and Chongqing without covering other parts of China and even other countries in the Asia-Pacific area. Fourth, due to practical influence, only part of the validation cohort (742 out of 1201 participants) received FIT, partially causing selection bias in evaluating the efficiency of the combined use of the modified score and FIT. Therefore, further investigation is needed to make the primary screening of ACN in China more precise and practical.

In summary, our study established a modified APCS score based on age, BMI, family history, diabetes, smoking and drinking and indicated that its use combined with FIT is efficient in selecting a high-risk group for CRC from a Chinese asymptomatic population to decrease the workload and optimize the resources of CRC screening for clinical practitioners and government policymakers.