Young colorectal cancer patients often present too late

Characteristics and symptomatology of colorectal cancer in the young

BACKGROUND

The incidence of colorectal cancer in patients <50 years has rapidly risen recently. Understanding the presenting symptoms may facilitate earlier diagnosis. We aimed to delineate patient characteristics, symptomatology, and tumor characteristics of colorectal cancer in a young population.

METHODS

A retrospective cohort study was conducted evaluating patients <50 years diagnosed between 2005 and 2019 with primary colorectal cancer at a university teaching hospital. The number and character of colorectal cancer-related symptoms at presentation was the primary outcome measured. Patient and tumor characteristics were also collected.

RESULTS

Included were 286 patients with a median age of 44 years, with 56% <45 years. Nearly all patients (95%) were symptomatic at presentation, with 85% having 2 or more symptoms. The most common symptoms were pain (63%), followed by change in stool habits (54%), rectal bleeding (53%), and weight loss (32%). Diarrhea was more common than constipation. More than 50% had symptoms for at least 3 months before diagnosis. The number and duration of symptoms were similar in patients older than 45 compared to those younger. Most cancers were left-sided (77%) and advanced stage at presentation (36% stage III, 39% stage IV).

CONCLUSION

In this cohort of young patients with colorectal cancer, the majority presented with multiple symptoms having a median duration of 3 months. It is essential that providers be mindful of the ever-increasing incidence of colorectal malignancy in young patients, and that those with multiple, durable symptoms should be offered screening for colorectal neoplasms based on symptoms alone.

Demographic and clinico-pathological characteristics of colorectal cancer in Kirkuk governorate, Iraq

BACKGROUND

World-wide Colorectal cancer (CRC) is the third most common cancer with one million new cases a year. Historically, a higher incidence of this disease has been recorded among the elderly in the western countries, but it is increasing in developing countries and in younger age groups.

AIM

This study aims to find whether CRC cancer is progressively affecting the younger age groups known as early onset (< 50 years). In addition, it describes the pathological characteristics of CRC in early onset CRC cases.

METHOD

The study is retrospective cross-sectional. It was conducted over a period of five months from October 1st 2019 till 1st March 1st 2020. Data were drawn from patients with CRC from their medical records at Kirkuk Oncology Centre (KOC) and from the IRAQI National CANCER REGISTRY (INCR) over thirteen years period from 2006 to 2018. The basic data we obtained for each patient include sex, age, and stage, grade of the disease at diagnosis and mode of presentation.

RESULTS

The Initial study population included 654 patients of both genders and all ages. CRC occurred in < 5.5/100,000 population per year which accounted for < 8% of total malignancies (2006-2018). The patients were divided into two groups; an early onset (< 50 years) group and a late onset CRC (⩾ 50 years) group. The final study population provided enough data for 238 patients for the years (2014-2018) with an age range of 20-91 and a mean of 54.4 years. The males were ∼54% while ∼46% were females. The age group under 50 years (early onset CRC) was ∼41% (no 98) while those who are 50 years and older (late onset) stood for 59% (no 140). There were no statistical differences between the two age groups regarding stage, grade, or presenting symptom.

CONCLUSION

CRC is common in early onsets or young age groups with similar pathological characteristics to those of the late onset cancer. Accordingly, even mild lower gastrointestinal symptoms should be taken seriously. The study points toward an increasing awareness of the population on the importance of colorectal cancer. Also, conducting more surveillance studies and investigations would be recommended for early detections of the disease in young populations.

Application of machine learning in the prediction of deficient mismatch repair in patients with colorectal cancer based on routine preoperative characterization

Simple summary

Detecting deficient mismatch repair (dMMR) in patients with colorectal cancer is essential for clinical decision-making, including evaluation of prognosis, guidance of adjuvant chemotherapy and immunotherapy, and primary screening for Lynch syndrome. However, outside of tertiary care centers, existing detection methods are not widely disseminated and highly depend on the experienced pathologist. Therefore, it is of great clinical significance to develop a broadly accessible and low-cost tool for dMMR prediction, particularly prior to surgery. In this study, we developed a convenient and reliable model for predicting dMMR status in CRC patients on routine preoperative characterization utilizing multiple machine learning algorithms. This model will work as an automated screening tool for identifying patients suitable for mismatch repair testing and consequently for improving the detection rate of dMMR, while reducing unnecessary labor and cost in patients with proficient mismatch repair.

Background

Deficient mismatch repair (dMMR) indicates a sustained anti-tumor immune response and has a favorable prognosis in patients with colorectal cancer (CRC). Although all CRC patients are recommended to undergo dMMR testing after surgery, current diagnostic approaches are not available for all country hospitals and patients. Therefore, efficient and low-cost predictive models for dMMR, especially for preoperative evaluations, are warranted.

Methods

A large scale of 5596 CRC patients who underwent surgical resection and mismatch repair testing were enrolled and randomly divided into training and validation cohorts. The clinical features exploited for predicting dMMR comprised the demographic characteristics, preoperative laboratory data, and tumor burden information. Machine learning (ML) methods involving eight basic algorithms, ensemble learning methods, and fusion algorithms were adopted with 10-fold cross-validation, and their performance was evaluated based on the area under the receiver operating characteristic curve (AUC) and calibration curves. The clinical net benefits were assessed using a decision curve analysis (DCA), and a nomogram was developed to facilitate model clinical practicality.

Results

All models achieved an AUC of nearly 0.80 in the validation cohort, with the stacking model exhibiting the best performance (AUC = 0.832). Logistical DCA revealed that the stacking model yielded more clinical net benefits than the conventional regression models. In the subgroup analysis, the stacking model also predicted dMMR regardless of the clinical stage. The nomogram showed a favorable consistence with the actual outcome in the calibration curve.

Conclusion

With the aid of ML algorithms, we developed a novel and robust model for predicting dMMR in CRC patients with satisfactory discriminative performance and designed a user-friendly and convenient nomogram.

Application of machine learning techniques in real-world research to predict the risk of liver metastasis in rectal cancer

Background

The liver is the most common site of distant metastasis in rectal cancer, and liver metastasis dramatically affects the treatment strategy of patients. This study aimed to develop and validate a clinical prediction model based on machine learning algorithms to predict the risk of liver metastasis in patients with rectal cancer.

Methods

We integrated two rectal cancer cohorts from Surveillance, Epidemiology, and End Results (SEER) and Chinese multicenter hospitals from 2010-2017. We also built and validated liver metastasis prediction models for rectal cancer using six machine learning algorithms, including random forest (RF), light gradient boosting (LGBM), extreme gradient boosting (XGB), multilayer perceptron (MLP), logistic regression (LR), and K-nearest neighbor (KNN). The models were evaluated by combining several metrics, such as the area under the curve (AUC), accuracy score, sensitivity, specificity and F1 score. Finally, we created a network calculator using the best model.

Results

The study cohort consisted of 19,958 patients from the SEER database and 924 patients from two hospitals in China. The AUC values of the six prediction models ranged from 0.70 to 0.95. The XGB model showed the best predictive power, with the following metrics assessed in the internal test set: AUC (0.918), accuracy (0.884), sensitivity (0.721), and specificity (0.787). The XGB model was assessed in the outer test set with the following metrics: AUC (0.926), accuracy (0.919), sensitivity (0.740), and specificity (0.765). The XGB algorithm also shows a good fit on the calibration decision curves for both the internal test set and the external validation set. Finally, we constructed an online web calculator using the XGB model to help generalize the model and to assist physicians in their decision-making better.

Conclusion

We successfully developed an XGB-based machine learning model to predict liver metastasis from rectal cancer, which was also validated with a real-world dataset. Finally, we developed a web-based predictor to guide clinical diagnosis and treatment strategies better.

Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

Background

Liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically.

Methods

We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model.

Results

A total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956).

Conclusion

We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02424-7.

Colorectal cancer of the young displays distinct features of aggressive tumor biology: A single-center cohort study

BACKGROUND

In recent years, a decrease in incidence and mortality of colorectal cancer (CRC) has been observed in developed nations, presumably through public disease awareness and increased screening efforts. However, a rising incidence of CRC in young patients below the age of 50 years has been reported in several studies.

AIM

To study tumor biology in CRC patients below 50 years of age.

METHODS

All patients with CRC were prospectively enrolled in our single-center oncologic database from January 2013 to December 2018 and were grouped and analyzed according to age (≥ 50 and < 50 years). Clinical as well as histopathological features were analyzed and compared. The study was approved by the local Ethics Committee. Fisher’s exact test or t-test was used to test for differences between the groups, as appropriate. All statistical analysis was performed with IBM SPSS software Version 25 (SPSS Inc, Armonk, NY, United States) and with R-Studio using R Version 3.4.1 (RStudio, Boston, MA, United States).

RESULTS

Seventeen percent of the 411 patients were younger than 50 years. Young patients were more often diagnosed with locally advanced T4-tumors and lymph node metastases (36.6% and 62% vs 17.7% and 42%; P < 0.01). In addition, a higher frequency of poorly differentiated (G3) tumors (40% vs 22.4% P < 0.05) was observed. More than every second patient below 40 years of age (51.8%) had distant metastases at diagnosis with a significant higher rate ring of signet cell differentiation compared to patients ≥ 50 years (14.8%, P < 0.05). Mutational status (KRAS, NRAS, BRAF, MSI) as well as selected behavioral risk factors showed no significant differences.

CONCLUSION

Distinct histopathologic features of increased biologic aggressiveness are found in patients with CRC of young-onset. Those patients present more frequently with more advanced tumor stages compared to older patients. Features of aggressive tumor biology underscore the need for earlier uptake of routine screening measures.

Is colorectal cancer associated with altered bowel habits in young patients?

BACKGROUND

There is a rising incidence in young-onset colorectal cancer, with these patients falling outside of routine screening programmes. The aim of the study is to characterize the nature of altered bowel habits in young patients who are diagnosed with colorectal cancer.

METHODS

A retrospective audit was conducted of adult patients younger than 45 years admitted under a Colorectal Surgery unit (Dandenong Hospital, Victoria) from 2011 to 2019 for the resection of colorectal cancer. We compared the patients' self-characterization of their bowel habits (from the medical record) with clinical and pathological data.

RESULTS

A total of 75 patients were identified, aged between 18 and 45 years, who had surgical resection of colonic or rectal adenocarcinoma between 2011 and 2019. Forty-two (56%) presented with altered bowel habit (irregular bowel habit n = 13, 17%; constipation n = 13, 17%; diarrhoea n = 23, 31%). Constipation approached significance in association with left-sided colonic cancer. Fatigue approached significance in association with right-sided colonic cancers, which were less likely to present with bleeding or constipation, and approached significance in being less likely to present with diarrhoea. Rectal cancers were more likely to present with bleeding.

CONCLUSION

Constipation was associated with left-sided colonic cancers, while right-sided colonic cancers were less likely to present with either constipation or diarrhoea. Our findings reinforce the need for clinicians to consider colorectal cancer as a differential diagnosis in young patients with altered bowel habits, or in patients with fatigue in the absence of specific bowel symptoms. Further prospective research is needed to further define bowel habits in this cohort.

The association of age with the clinicopathological characteristics and prognosis of colorectal cancer: a UK single-centre retrospective study

INTRODUCTION

Colorectal cancer (CRC) is uncommon in patients under the age of 40 years and its association with poor histological features and survival is uncertain. This study aimed to evaluate age-related differences in clinicopathological features and prognosis in patients diagnosed with CRC.

METHOD

A single-centre retrospective review of all patients diagnosed with CRC between 2004 and 2013 was performed. Patients were stratified into three age groups: (1) 18-40 years, (2) 41-60 years and (3)> 60 years. Clinicopathological characteristics and outcomes were compared between the three groups.

RESULTS

A total of 1328 patients were included, of whom 57.2% were men. There were 28 (2.1%) patients in group 1, 287 (21.6%) in group 2 and 1013 (76.3%) in group 3. Group 1 had the highest proportion of rectal tumours (57.1% in group 1, 50.2% in group 2 and 31.9% in group 3; P < 0.001). Tumour histology and disease stage were comparable between the groups. Group 1 had significantly worse disease-free survival (DFS) than the two older groups (44%, 78% and 77%, respectively; P = 0.022). Multivariate analysis demonstrated that age was not an independent prognostic factor whereas Stage III disease [hazard ratio (HR) 4.42; 95% CI 2.81-6.94; P < 0.001] and neoadjuvant chemotherapy (HR 1.65; 95% CI 1.06-2.58; P = 0.026) were associated with increased risk of recurrence.

CONCLUSION

Patients under the age of 40 are more likely to present with rectal cancer and have comparable histological features than the older groups. Despite higher rates of adjuvant and neoadjuvant treatment, the young group were found to have worse DFS.

The long-term survival characteristics of a cohort of colorectal cancer patients and baseline variables associated with survival outcomes with or without time-varying effects

BACKGROUND

Colorectal cancer is the third most common cancer in the world. In this study, we assessed the long-term survival characteristics and prognostic associations and potential time-varying effects of clinico-demographic variables and two molecular markers (microsatellite instability (MSI) and BRAF Val600Glu mutation) in a population-based patient cohort followed up to ~ 19 years.

METHODS

The patient cohort included 738 incident cases diagnosed between 1999 and 2003. Cox models were used to analyze the association between the variables and a set of survival outcome measures (overall survival (OS), disease-specific survival (DSS), recurrence-free survival (RFS), metastasis-free survival (MFS), recurrence/metastasis-free survival (RMFS), and event-free survival (EFS)). Cox proportional hazard (PH) assumption was tested for all variables, and Cox models with time-varying effects were used if any departure from the PH assumption was detected.

RESULTS

During the follow-up, ~ 61% patients died from any cause, ~ 26% died from colorectal cancer, and ~ 10% and ~ 20% experienced recurrences and distant metastases, respectively. Stage IV disease and post-diagnostic recurrence or metastasis were strongly linked to risk of death from colorectal cancer. If a patient had survived the first 6 years without any disease-related event (i.e., recurrence, metastasis, or death from colorectal cancer), their risks became very minimal after this time period. Distinct sets of markers were associated with different outcome measures. In some cases, the effects by variables were constant throughout the follow-up. For example, MSI-high tumor phenotype and older age at diagnosis predicted longer MFS times consistently over the follow-up. However, in some other cases, the effects of the variables varied with time. For example, adjuvant radiotherapy treatment was associated with increased risk of metastasis in patients who received this treatment after 5.5 years post-diagnosis, but not before that.

CONCLUSIONS

This study describes the long-term survival characteristics of a prospective cohort of colorectal cancer patients, relationships between baseline variables and a detailed set of patient outcomes over a long time, and time-varying effects of a group of variables. The results presented advance our understanding of the long-term prognostic characteristics in colorectal cancer and are expected to inspire future studies and clinical care strategies.

Curative treatment for metastatic colorectal cancer in the young population: is it worth it?

Background

A significant proportion of patients with colorectal cancer (CRC) presents with metastatic disease. In younger patients, a more aggressive approach is often adopted in an attempt to achieve cure and improve survival. The aim of this paper is to review the management and outcomes of young patients with metastatic CRC.

Methods

All patients under 50 years diagnosed with CRC in a single institution from January 2007 to December 2015 were reviewed. Patient demographics, details of their treatments, progress and outcomes of treatment were collected for our review.

Results

There were 154 newly diagnosed CRC patients who were <50 years old during the study period. Thirty-three patients (21.4%) had stage IV disease on presentation. Seventeen (51.5%) of these 33 patients were treated with curative intent; 9 (52.9%) of whom underwent upfront surgical resection alone while the remaining 8 (47.1%) patients had neoadjuvant therapy followed by surgical resection. Among the 16 patients who were treated with palliative intent, 9 (56.3%) had surgery while 7 (43.7%) had definitive chemo- or radio-therapy. There was no significant difference in the median survival of patients treated with curative and palliative intent (29 vs. 24 months, P=0.140).

Conclusions

Young CRC patients with stage IV disease typically survive for 2 years upon diagnosis. Those who were treated and underwent surgery with curative intent have a slightly longer but not statistically significant median survival than those treated with palliative intent. The role of aggressive treatment in these young patients with metastatic patients merits further evaluation.