Abstract
Background:
Early-onset colorectal cancer (EOCC), defined as CRC in patients under 50, is rising alarmingly in Western countries. This study explores key differences in clinical profiles, socioeconomic factors, and oncological treatments between EOCC and later-onset colorectal cancer (LOCC) patients.
Patients and methods:
This multicenter cohort study analyzed CRC patients treated from January 2023 to June 2024 at 11 centers in Northwestern Switzerland. Patients with confirmed CRC were included, while exclusions applied to secondary CRC, unconfirmed cases, and those unable to consent. Statistical analyses included descriptive methods, Fisher’s exact test, Kruskal–Wallis tests, and logistic regression (P ≤ 0.05).
Results:
Among 764 patients, 10.5% had EOCC and 89.5% LOCC. Mean age was 42.1 for EOCC and 70.8 for LOCC. EOCC patients were more often non-Swiss (67.5% vs. 32.2%, P < 0.001), faced greater financial hardship (P < 0.001), consumed more glucose (>5 units/week) (48.8% vs. 35.2%, P = 0.02), and had more second-degree relatives with CRC (P = 0.05). EOCC symptoms included abdominal pain (54.6%) and rectal bleeding (50.6%), while LOCC presented with rectal bleeding (35.4%) and bowel habit changes (25.3%). EOCC had longer diagnostic delays (7.2 vs. 4.2 months, P = 0.03) and reached a higher UICC stage (IIIC vs. IIIA). Adjuvant therapy was more frequent in EOCC for colon (52.4% vs. 35.2%, P = 0.04) and rectal cancer (58.3% vs. 33.3%, P = 0.02). Defunctioning ostomies were more common in EOCC (13.2% vs. 3.2%, P = 0.01). EOCC had shorter hospital stays (8.66 vs. 11.43 days, P = 0.05), but intensive care unit stays, complications, lymph node retrieval, and operation times were similar.
Conclusion:
These findings emphasize the need for tailored screening protocols and personalized management strategies to address the unique challenges faced by patients under 50 and to improve outcomes.
Keywords: colorectal cancer (CRC), diagnostic delay, early-onset colorectal cancer (EOCC), late-onset colorectal cancer (LOCC), risk factors, symptoms
Introduction
While colorectal cancer (CRC) rates and mortality have declined among older adults in many high-income countries due to advancements in screening and treatment, recent data highlight an alarming rise in CRC incidence among individuals under the age of 50, particularly in Western nations such as the USA, Australia, Canada, and Norway[1–3].
Indeed, the incidence of early-onset colorectal cancer (EOCC), defined as diagnosis before age 50, has surged by up to 60% in recent decades across these regions[4]. This trend places heavy social and economic burdens on patients and their families, especially when patients are caregivers, driving up healthcare costs, income loss, and emotional distress, emphasizing the need for policies addressing the broader consequences of EOCC[5].
Recent studies have associated EOCC with lifestyle factors prevalent in Western societies, including obesity, physical inactivity, and high-fat diets[6,7]. These factors may drive metabolic changes, such as insulin resistance and chronic inflammation, which are thought to contribute to CRC development[6,7].
Approximately one-third of EOCC cases are associated with germline mutations, enabling early detection in individuals with a known familial risk. However, the majority of EOCC cases are diagnosed symptomatically and fall outside routine screening programs[8].
Abdominal pain, rectal bleeding, and altered bowel habits strongly indicate CRC risk in older patients[9–11]. In younger patients, symptoms such as rectal bleeding – often misattributed to hemorrhoids – or abdominal cramps, frequently mistaken for irritable bowel syndrome (IBS), commonly result in delayed diagnosis. This delay enables disease progression to advanced and aggressive stages, increasing the likelihood of metastasis and contributing to poorer clinical outcomes[12]. Moreover, current treatment protocols for CRC, primarily developed for older populations, may not be fully applicable to younger patients with EOCC[13]. EOCC patients often present with more aggressive and poorly differentiated tumors. Despite undergoing more radical, guideline-compliant therapies, these treatments fail to provide the same survival benefits seen in older patients[14–16].
The rising incidence and mortality of EOCC in younger populations highlight the need for tailored clinical guidelines and treatment strategies. The recent shift in U.S. screening recommendations to age 45 reflects this trend, emphasizing the importance of adapting public health measures to evolving disease patterns[17,18].
To address the growing challenges of EOCC, this project investigates key differences in time to diagnosis (diagnostic delay), clinical presentation, socioeconomic influences, and oncological treatment strategies between EOCC and LOCC. By identifying the factors driving the unique outcomes of EOCC patients, this initiative aims to refine treatment protocols, improving both the management and prognosis of those affected by this increasingly prevalent condition.
Patients and methods
Study design
In adherence to the STROCSS guidelines, this multicenter study prospectively enrolled all patients seeking oncologic treatment for CRC between January 1, 2023 and June 30, 2024[19].
The study was conducted across the Clarunis Hospital Network, which includes eleven hospitals spanning the extended Northwestern Switzerland region, from reference centers to mid-sized cantonal hospitals.
Data collection
Patient data, encompassing medical records and responses to a study-specific questionnaire on symptom-related concerns and quality of life, were collected by the local principal investigator or their designee at each institution. This information was then stored in a centralized database using Research Electronic Data Capture, a web-based platform for research data collection and management.
HIGHLIGHTS
Early-onset colorectal cancer (EOCC) patients experience significantly longer diagnostic delays (7.2 vs. 4.2 months for late-onset colorectal cancer [LOCC], P = 0.03), highlighting the need for earlier detection.
Despite red-flag symptoms like rectal bleeding (50.6% vs. 36.3% in older patients), abdominal pain, fatigue, and diarrhea, EOCC patients experience significantly longer diagnostic delays.
A higher prevalence of irritable bowel syndrome in EOCC patients (12.12% vs. 4.63% in LOCC, P = 0.019) may contribute to misdiagnosis, delaying timely EOCC diagnosis.
High intake of sugar-sweetened beverages as a risk factor for CRC was more prevalent in EOCC than in LOCC patients (P < 0.001).
Patients completed a questionnaire adapted from the EORTC QLQ-C30[20] and EORTC QLQ-CR29[21] quality of life instruments, with the addition of three socio-demographic questions specific to this study. The questionnaire addressed four key domains: (I) general health, (II) CRC–related symptoms and issues, (III) general inquiries, and (IV) time of diagnosis. This tailored instrument facilitated the collection of patient-reported outcomes to assess the quality of CRC care, thereby informing targeted quality improvement efforts and promoting personalized, high-quality care within healthcare settings.
To protect patient privacy and maintain confidentiality, all collected data were anonymized. The database was hosted on servers at the University Hospital Basel, ensuring secure access to data across all 11 participating hospitals. Upon enrollment, patients were stratified into two age cohorts: those under 50 years (EOCC) and those aged 50 years and older (LOCC).
Inclusion criteria
Eligible patients were defined as individuals aged 18 years or older with a recent diagnosis of CRC who were seeking oncological treatment. All cancer stages and treatment modalities, including palliative care, were permitted. Additionally, patients were required to provide general consent for the use of their clinical data in research.
Exclusion criteria
Exclusion criteria included patients younger than 18 years, those lacking a confirmed diagnosis of CRC, and individuals with CRC secondary to another primary malignancy (e.g. colorectal metastasis originating from a different primary tumor). Patients who did not provide general consent for data use were also excluded. Patients who were unable to complete the questionnaire due to cognitive limitations or language barriers were also excluded.
Statistical analysis
Data were analyzed using appropriate descriptive statistics, mean, standard deviation, and interquartile range for continuous variables and frequency and percentages for categorical variables. Comparison between binary outcomes was made using Fisher’s exact test for categorical and Kruskal–Wallis’ test for continuous variables. A multiple model to profile EOCC versus LOCC patients was fitted using logistic regression analysis, retaining independent covariates that remained statistically significant in a backward manual removal process.
Two-sided P-values ≤0.05 were considered statistically significant. Analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).
Primary and secondary endpoints
The primary objective was to evaluate whether the EOCC group experienced a delay in diagnosis compared to the LOCC group.
The secondary objective was to analyze risk factors, including demographic characteristics, CRC-specific symptoms, and treatment modalities, that differed between the two age cohorts.
Results
Patient characteristics and socioeconomic status (Table 1 and Supplemental Digital Content 1, available at: http://links.lww.com/JS9/E651).
Table 1.
Patient characteristics and socioeconomic status
| Variable | EOCC, N = 80 | LOCC, N = 684 | P-value | ||||
|---|---|---|---|---|---|---|---|
| Mean age | 42.1 | 70.8 | N/A | ||||
| Sex | n | abs. | % | n | abs. | % | abs. |
| Female | 80 | 33 | 41.3 | 681 | 280 | 41.1 | >0.99 |
| Male | 47 | 58.8 | 401 | 58.9 | |||
| Nationality | n | abs. | % | n | abs. | % | abs. |
| Swiss | 77 | 52 | 67.5 | 651 | 552 | 84.8 | <0.001 |
| Non-Swiss | 25 | 32.5 | 99 | 15.2 | |||
| ASA Score distribution I/II | n | abs. | % | n | abs. | % | abs. |
| I/II | 74 | 40 | 54.1 | 615 | 222 | 36.1 | 0.003 |
| III/IV | 34 | 45.9 | 393 | 63.9 | |||
| Comorbidities | n | abs. | % | n | abs. | % | abs. |
| Cardiovascular disease | 79 | 10 | 12.7 | 675 | 233 | 34.5 | <0.001 |
| Diabetes mellitus | 79 | 3 | 3.8 | 670 | 109 | 16.3 | 0.001 |
| Risk factors related to CRC | n | abs. | % | n | abs. | % | abs. |
| Childhood radiation exposure | 80 | 71 | 88.8 | 684 | 647 | 94.6 | 0.05 |
| Sugar intake | n | abs. | % | n | abs. | % | abs. |
| No sugar | 80 | 30 | 37.5 | 684 | 342 | 50.0 | 0.04 |
| Sugar (at least once a week) | 50 | 62.5 | 342 | 50.0 | |||
| Glucose/fructose intake | n | abs. | % | n | abs. | % | abs. |
| Low (<5/week) | 80 | 41 | 51.3 | 668 | 433 | 64.8 | 0.02 |
| High (>5/week) | 80 | 39 | 48.8 | 668 | 234 | 35.0 | |
| Protective factors related to CRC | n | abs. | % | n | abs. | % | abs. |
| Aspirin use | 78 | 1 | 1.3 | 664 | 117 | 17.6 | <0.001 |
| Vegetarian | 80 | 9 | 11.3 | 684 | 37 | 5.4 | 0.05 |
| Vegan diet | 80 | 1 | 1.3 | 684 | 2 | 0.3 | 0.28 |
| Education level | n | abs. | % | n | abs. | % | abs. |
| University diploma | 78 | 39 | 50.0 | 664 | 432 | 65.1 | <0.001 |
abs. = absolute value
A total of 764 patients were analyzed, comprising 10.5% EOCC and 89.5% LOCC.
The mean age for EOCC was 42.1 years, compared to 70.8 years for LOCC. The sex distribution was comparable between the groups, with females representing 41.3% of EOCC patients and 41.1% of LOCC patients, and males accounting for 58.8% of EOCC patients and 58.9% of LOCC patients (P > 0.99).
A higher proportion of EOCC patients were non-Swiss compared to LOCC patients (32.5% vs. 15.2%, P < 0.001), and EOCC patients more frequently reported financial hardship (Supplemental Digital Content Table 1, available at: http://links.lww.com/JS9/E651, P < 0.001). Financial hardship was assessed as a subjective, patient-reported outcome based on responses to the question: “Has your physical condition or medical treatment caused you financial difficulties?,” rated on a scale from “not at all” to “very much.”
Radiation exposure in childhood was higher in the LOCC group with 94.6% compared to 88.8% in the EOCC group (P = 0.05). Glucose intake was significantly higher in EOCC patients, with 48.8% consuming more than five units of fructose or glucose per week, compared to 35% of LOCC patients (P = 0.02).
Clinical and diagnostic features (Table 2)
Table 2.
Clinical and diagnostic features
| Variable | EOCC, N = 80 | LOCC, N = 684 | P-value | ||||
|---|---|---|---|---|---|---|---|
| Symptoms | n | abs. | % | n | abs. | % | abs. |
| Rectal bleeding | 79 | 40 | 50.6 | 641 | 233 | 36.3 | 0.02 |
| Rectal mucous discharge | 76 | 21 | 27.6 | 626 | 81 | 12.9 | 0.002 |
| Painful defecation | 74 | 7 | 9.5 | 626 | 48 | 7.7 | 0.65 |
| Abdominal pain | 77 | 42 | 54.5 | 632 | 159 | 25.2 | <0.001 |
| Rectal pain | 75 | 9 | 12.0 | 626 | 52 | 8.3 | 0.28 |
| Weight loss | 74 | 12 | 16.2 | 626 | 128 | 20.4 | 0.3 |
| Ileus | 79 | 5 | 6.3 | 627 | 33 | 5.3 | 0.58 |
| Incontinence | 73 | 1 | 1.4 | 625 | 24 | 3.8 | 0.5 |
| Change in bowel habits | 75 | 28 | 37.3 | 636 | 161 | 25.3 | 0.04 |
| Diarrhea | 75 | 30 | 40.0 | 641 | 161 | 25.1 | 0.008 |
| Constipation | 73 | 16 | 21.9 | 637 | 117 | 18.4 | 0.43 |
| Nausea | 74 | 11 | 14.9 | 625 | 44 | 7.0 | 0.04 |
| Reduced appetite | 74 | 13 | 17.6 | 626 | 82 | 13.1 | 0.28 |
| Bloating | 74 | 26 | 35.1 | 622 | 91 | 14.6 | <0.001 |
| Food intolerance | 74 | 0 | 0.0 | 612 | 9 | 1.5 | 0.06 |
| Fatigue | 75 | 32 | 42.7 | 627 | 175 | 27.9 | 0.01 |
| Other | 72 | 10 | 13.9 | 621 | 95 | 15.3 | 0.86 |
| Mode of diagnosis | n | abs. | % | n | abs. | % | abs. |
| CT | 74 | 22 | 29.7 | 670 | 134 | 20.0 | 0.12 |
| Endoscopy | 49 | 66.2 | 511 | 76.3 | |||
| MRI | 0 | 0.0 | 11 | 1.6 | |||
| Ultrasound | 1 | 1.4 | 4 | 0.6 | |||
| Clinical | 2 | 2.7 | 10 | 1.5 | |||
abs. = absolute value
In the EOCC group, the most frequent symptoms were abdominal pain (54.5%), rectal bleeding (50.6%), fatigue (42.7%), and diarrhea (40%). In contrast, LOCC patients presented with rectal bleeding (36.3%), changes in bowel habits (25.3%), abdominal pain (25.2%), and diarrhea (25.1%).
To differentiate CRC-related symptoms from those related to IBS, we defined IBS as symptoms lasting over 24 months. For the sub-analysis of CRC-related symptoms, only those persisting for less than 12 months were included[22]. All reported symptom durations were based on patient recollection.
IBS occurred more often in the EOCC group compared to the LOCC group, with rates of 12.1% and 4.6%, respectively (P = 0.02).
Endoscopy was the primary diagnostic tool for both groups (66.2% in EOCC vs. 76.3% in LOCC), followed by CT scans (29.7% in EOCC vs. 20% in LOCC).
To explore diagnostic approaches potentially impacting diagnostic delay, we analyzed the reasons for investigations between the two age groups. In the EOCC group, 85.3% underwent further investigations due to symptoms, compared to 68.7% in the LOCC group. Screening colonoscopies accounted for 23.5% of investigations in the LOCC group but only 8% in the EOCC group. Incidental findings were observed in 6.7% of EOCC cases and 7.8% of LOCC cases.
Diagnostic delay was defined as the period between the onset of initial CRC-related symptoms (duration <12 months) and the final diagnosis[23]. The average time for EOCC patients to diagnosis was 7.2 months, compared to 4.2 months for LOCC patients (P = 0.03).
Tumor characteristics and localization (Table 3, Supplemental Digital Content 1, available at: http://links.lww.com/JS9/E651).
Table 3.
Tumor localization and characteristics
| Variable | EOCC, N = 80 | LOCC, N = 684 | ||||
|---|---|---|---|---|---|---|
| Tumor localization | n | abs. | % | n | abs. | % |
| Right | 76 | 12 | 15.8 | 669 | 198 | 29.6 |
| Transverse | 5 | 6.6 | 47 | 7.0 | ||
| Left | 28 | 36.8 | 167 | 25.0 | ||
| Total colonic tumor | 45 | 59.2 | 412 | 61.6 | ||
| Rectum | 31 | 40.8 | 257 | 38.4 | ||
| T-status (postoperative) | n | abs. | % | n | abs. | % |
| T0 | 80 | 7 | 8.8 | 684 | 16 | 2.3 |
| T1 | 12 | 15.0 | 104 | 15.2 | ||
| T2 | 7 | 8.8 | 121 | 17.7 | ||
| T3 | 25 | 31.3 | 252 | 36.8 | ||
| T4 | 12 | 15.0 | 98 | 14.3 | ||
| Tx | 17 | 21.3 | 93 | 13.6 | ||
| N-status (postoperative) | n | abs. | % | n | abs. | % |
| N0 | 80 | 34 | 42.5 | 684 | 376 | 55.0 |
| N1 | 13 | 16.3 | 136 | 19.9 | ||
| N2 | 13 | 16.3 | 63 | 9.2 | ||
| Nx | 20 | 25.0 | 109 | 15.9 | ||
| M-status (postoperative) | n | abs. | % | n | abs. | % |
| M0 | 80 | 42 | 52.5 | 684 | 401 | 58.6 |
| M1 | 11 | 13.8 | 59 | 8.6 | ||
| M2 | 18 | 22.5 | 81 | 11.8 | ||
| Mx | 9 | 11.3 | 143 | 20.9 | ||
| UICC stages (postoperative) | n | abs. | % | n | abs. | % |
| 0 | 62 | 5 | 8.1 | 584 | 15 | 2.6 |
| IA | 9 | 14.5 | 76 | 13.0 | ||
| IB | 5 | 8.1 | 95 | 16.3 | ||
| IIA | 11 | 17.7 | 135 | 23.1 | ||
| IIB | 3 | 4.8 | 34 | 5.8 | ||
| IIIA | 8 | 12.9 | 103 | 17.6 | ||
| IIIB | 4 | 6.5 | 21 | 3.6 | ||
| IIIC | 6 | 9.7 | 43 | 7.4 | ||
| IV | 11 | 17.7 | 62 | 10.6 | ||
| G-status (postoperative) | n | abs. | % | n | abs. | % |
| G1 | 80 | 5 | 6.3 | 684 | 74 | 10.8 |
| G2 | 38 | 47.5 | 389 | 56.9 | ||
| G3 | 13 | 16.3 | 72 | 10.5 | ||
| Gx | 24 | 30.0 | 149 | 21.8 | ||
abs. = absolute value
In the EOCC group, 59.2% of tumors were colonic and 40.8% rectal, while in the LOCC group, 61.6% were colonic and 38.4% rectal. Tumor characteristics were staged using the AJCC 8th edition of the TNM classification[24]. Postoperative T-stage distribution was similar, with T3 tumors observed in 31.3% of EOCC and 36.8% of LOCC cases. The number of lymph nodes retrieved was not significantly different between both groups: 30.8 in EOCC and 27.3 in LOCC (P = 0.5, Supplemental Digital Content 1, available at, http://links.lww.com/JS9/E651). However, our data revealed a higher likelihood of advanced nodal disease (N2, 16.3%) in EOCC compared to LOCC (N2, 9.2%) and metastatic burden was present in 36.3% of EOCC patients, compared to 20.5% in the LOCC group. Based on these findings, the most frequent UICC stages in EOCC were stage IIA and IV (both 17.7%), while in LOCC, stage IIA was most common (23.1%). At the 75th percentile, EOCC reached a higher UICC stage (IIIC) compared to LOCC (IIIA).
Perioperative data (neoadjuvant and adjuvant systemic therapy, surgical techniques, and postoperative complication) for colon cancer patients (Table 4)
Table 4.
Perioperative data (neoadjuvant and adjuvant systemic therapy, surgical techniques, and postoperative complication) for colon cancer patients
| Variable | EOCC colon, N = 49 | LOCC colon, N = 427 | P-value | ||||
|---|---|---|---|---|---|---|---|
| Type of surgery | n | abs. | % | n | abs. | % | abs. |
| Open | 47 | 8 | 17.0 | 425 | 102 | 24.0 | N/A |
| Laparoscopic | 18 | 38.3 | 193 | 45.4 | |||
| Robotic | 10 | 21.3 | 83 | 19.5 | |||
| Conversion | 3 | 6.4 | 21 | 4.9 | |||
| Anastomosis formed? | n | abs. | % | n | abs. | % | abs. |
| Yes | 39 | 39 | 100 | 377 | 347 | 92.0 | 0.1 |
| No | 0 | 0 | 30 | 8.0 | |||
| If anastomois performed, presence of defunctioning ileostomy? | n | abs. | % | n | abs. | % | abs. |
| Yes | 38 | 5 | 13.2 | 344 | 11 | 3.2 | 0.01 |
| No | 33 | 86.8 | 333 | 97 | |||
| If yes, presence of defunctioning ostomy? | n | abs. | % | n | abs. | % | abs. |
| Loop ileostomy | 5 | 3 | 60 | 11 | 4 | 36.4 | 0.61 |
| Loop transverstomy | 1 | 20 | 1 | 9.1 | |||
| Split stoma | 1 | 20 | 1 | 9.1 | |||
| End colostomy | 0 | 0 | 2 | 18.2 | |||
| End ileostomy | 0 | 0 | 3 | 27.3 | |||
| Complications | n | abs. | % | n | abs. | % | abs. |
| Major (IIIB, IV, V) | 49 | 2 | 4.1 | 427 | 38 | 8.9 | 0.41 |
| Reoperation within 30 days | n | abs. | % | n | abs. | % | abs. |
| Reoperation within 30 days | 40 | 4 | 10.0 | 372 | 43 | 11.6 | >0.99 |
abs. = absolute value
In the EOCC group, laparoscopic surgery was performed in 38.3%, robotic in 21.3%, and open in 17.0%, compared to 45.4%, 19.5%, and 24.0% in the LOCC group, respectively.
Anastomosis was performed in 100% of EOCC cases and 92.0% of LOCC cases (P = 0.1).
Major complications (Clavien-Dindo > IIIB) did not occur significantly more often in LOCC patients with colonic tumors (38/427, 8.9%) compared to EOCC patients (2/49, 4.1%, P = 0.41).
Perioperative data (neoadjuvant and adjuvant systemic therapy, surgical techniques, and postoperative complication) for rectal cancer patients (Table 5)
Table 5.
Perioperative data (neoadjuvant and adjuvant systemic therapy, surgical techniques, and postoperative complication) for rectal cancer patients
| Variable | EOCC rectum, N = 31 | LOCC rectum, N = 257 | P-value | ||||
|---|---|---|---|---|---|---|---|
| Type of surgery | n | abs. | % | n | abs. | % | abs. |
| Open | 31 | 2 | 6.5 | 257 | 24 | 9.3 | N/A |
| Laparoscopic | 6 | 19.4 | 88 | 34.2 | |||
| Robotic | 13 | 41.9 | 101 | 39.3 | |||
| Conversion | 0 | 0.0 | 8 | 3.1 | |||
| Anastomosis formed? | n | abs. | % | n | abs. | % | abs. |
| Yes | 20 | 17 | 85.0 | 208 | 173 | 83.2 | >0.99 |
| No | 3 | 15.0 | 35 | 16.8 | |||
| If anastomosis performed, presence of defunctioning ileostomy? | n | abs. | % | n | abs. | % | abs. |
| Yes | 16 | 7 | 43.8 | 169 | 57 | 33.7 | 0.42 |
| No | 9 | 56.3 | 112 | 66.3 | |||
| If yes, presence of defunctioning ostomy? | n | abs. | % | n | abs. | % | abs. |
| Loop Ileostomy | 7 | 7 | 100 | 56 | 44 | 78.6 | >0.99 |
| Loop transverstomy | 0 | 2 | 3.6 | ||||
| Split stoma | 0 | 1 | 1.8 | ||||
| End colostomy | 0 | 5 | 8.9 | ||||
| End ileostomy | 0 | 4 | 7.1 | ||||
| Complications | n | abs. | % | n | abs. | % | abs. |
| Major (IIIB, IV, V) | 31 | 4 | 12.9 | 257 | 26 | 10.1 | 0.55 |
| Reoperation within 30 days | n | abs.a | % | n | abs. | % | abs. |
| Reoperation within 30 days | 22 | 4 | 18.2 | 204 | 34 | 16.7 | >0.99 |
abs. = absolute value
Among EOCC patients with rectal cancer, robotic surgery was performed in 41.9%, laparoscopic in 19.4%, and open in 6.5%, compared to 39.3%, 34.2%, and 9.3% in the LOCC, respectively. A direct anastomosis was performed in 85.0% of EOCC cases and 83.2% of LOCC cases (P > 0.99). Defunctioning ostomy was more frequently performed in EOCC patients (43.8% vs. 33.7%, P = 0.42), with loop ileostomy being the most common type in both groups (100% EOCC vs. 78.6% LOCC).
Major complications (Clavien-Dindo IIIB-V) were comparable between EOCC and LOCC patients with rectal tumors: 12.9% (4/31) of EOCC versus 10.1% (26/257) of LOCC patients (P = 0.55).
Discussion
This comprehensive analysis, based on data from 11 national centers across the extended northwestern part of Switzerland, offers critical insights into the clinical characteristics and diagnostic challenges of EOCC patients compared to older individuals. Additionally, we conducted a qualitative study with selected patients through interviews to gain insights into their experiences during diagnosis and therapy. While this part of the study is still under revision, understanding both the clinical and personal aspects of EOCC is essential for improving diagnostic strategies, patient care, and developing tailored interventions for younger patients.
Our findings stress the substantial diagnostic delays (7.2 vs. 4.2 months, for EOCC and LOCC, respectively, P = 0.03) and unique clinical presentations in younger patients, emphasizing the need for increased awareness and earlier detection strategies for EOCC. These results highlight the pressing challenge of identifying EOCC in the younger populations, where timely diagnosis remains more elusive.
EOCC is often diagnosed at more advanced stages, with increased rates of locally advanced disease, lymph node involvement, and metastatic spread[25].
Consistent with previous studies[4,26], our findings show a higher prevalence of metastatic disease in EOCC patients compared to LOCC patients (36.3% vs. 23.3%).
In our study, patients with EOCC frequently reported severe symptoms, including abdominal pain, rectal bleeding, fatigue, and diarrhea. Notably, rectal bleeding was present in up to 50.6% of symptomatic young individuals, compared to 36.3% in older patients. This aligns with prior studies reporting rectal bleeding in up to 59% of young individuals with EOCC at diagnosis[27,28]. Despite the high prevalence of this red-flag symptom, diagnostic delays were significantly more common in younger patients.
On average, time to diagnosis for EOCC patients was 7.2 versus 4.2 months, for EOCC and LOCC, respectively (P = 0.03). This significant delay may be partially explained by the higher prevalence of IBS among EOCC patients (12.12% vs. 4.63%, P = 0.019), which could confound clinical suspicion and contribute to misdiagnosis.
Studies indicate an elevated risk of CRC detection within 1 year of an IBS diagnosis. Wu et al[22] reported significantly higher CRC risk ratios in IBS patients under 50 compared to those older than 50. In young individuals with EOCC, rectal bleeding is commonly misattributed to hemorrhoids, leading to diagnostic delays. This highlights the need for thorough evaluation, including colonoscopy, for individuals under 50 with hematochezia, as recommended by the American Society for Gastrointestinal Endoscopy and the European Panel on the Appropriateness of Gastrointestinal Endoscopy[29,30]. In Switzerland, population-wide screening starting at age 45 could prevent one death and three CRC cases per 1000 individuals screened, increasing CRC detection by 5%–6% and reducing deaths by 4%[30]. Targeting high-risk patients based on symptoms and risk factors, rather than universal screening, may be more efficient in optimizing healthcare resources, as discussed in the following sections.
Lifestyle factors play a critical role in the pathogenesis of EOCC. Each additional weekly report of higher sugar intake was associated with a 20% increased risk of EOCC (P < 0.001), highlighting the influence of dietary habits[31].
Our analysis of sugar consumption was based on questionnaire data that did not specifically inquire about sodas or other individual beverages but rather focused on the frequency of sugar and fructose intake, including products containing these sugars, measured weekly. The mention of sugar-sweetened beverages (SSBs), including juices or sodas, was introduced as a hypothesis to contextualize and interpret our findings, based on previous literature[32,33].
In our cohort, 62.5% of EOCC patients reported consuming sugar at least once a week, compared to 50.0% of LOCC patients (P = 0.04). Furthermore, nearly half of the EOCC group (48.8%) reported high glucose/fructose intake (>5 times per week), whereas only 35.0% of LOCC patients fell into this category (P = 0.02). These findings suggest a significant association between higher sugar intake and EOCC risk.
High sugar and SSB consumption during adolescence has been linked to increased adenoma risk[31], with global SSB consumption rising by 23% between 1990 and 2018, potentially contributing to the EOCC surge[32]. Women consuming two or more SSBs daily had over double the EOCC risk compared to those consuming fewer than one per week, underscoring the need for targeted public health measures[33]. A Western-style diet and obesity (BMI >30 kg/m2), both established CRC risk factors, also contribute to rising EOCC rates. In our study, 17.28% of participants had a BMI >30 kg/m2, predominantly in the ≥50 years group (85.59%), supporting the link between obesity and later-life CRC.
Rising CRC incidence, particularly rectal cancer, has been noted in non-Hispanic White, Hispanic, and Black populations, with Black men and women experiencing the largest increases[34,35]. These disparities likely reflect lifestyle factors, socioeconomic status, and healthcare access, influencing CRC incidence and outcomes[16].
In our cohort, EOCC patients were more likely to be non-Swiss nationals compared to LOCC patients, reflecting demographic trends in Switzerland, where younger age groups include a higher proportion of individuals with a migration background[36]. Due to restrictive naturalization policies, many remain non-citizens despite long-term residence. This group is also more frequently exposed to structural socioeconomic disadvantages, which may contribute to the higher prevalence of financial hardship observed among EOCC patients[37]. Despite mandatory health insurance in Switzerland, out-of-pocket expenses, such as premiums, deductibles, and co-payments, may hinder timely access to care for low-income populations and recent migrants. This underscores that universal coverage does not automatically ensure equitable healthcare access.
Treatment strategies, including neoadjuvant therapy, surgery, and adjuvant therapy, were comparable between groups, except for a higher use of adjuvant treatments among EOCC patients (P = 0.018). Specifically, EOCC patients were more likely to have node-positive disease and to receive adjuvant chemotherapy compared to LOCC patients (92.3% vs. 71.4%, P = 0.030). In the subset of patients with T3 rectal carcinomas and node-positive status, adjuvant chemotherapy use remained higher in the EOCC group (85.7% vs. 65.8%), though this difference was not statistically significant (P = 0.4069).
This may reflect a greater willingness among younger patients to pursue aggressive treatments, even with marginal benefit and potential risks. Relapse-free survival rates for stage II and III CRC were consistent with historical clinical trial data across all age groups[38].
Surgical approaches were also similar, with minimally invasive techniques being the predominant method in both groups. The use of robotic surgery was comparable across age groups (29.5% EOCC vs. 27.0% LOCC, P = 0.2443), with no significant differences observed between centers (P = 0.2542) or in the interaction between center and surgical approach (P = 0.3438), indicating consistent adoption of robotic techniques regardless of patient age or treatment location.
Limitations
This study has several limitations that should be considered when interpreting the findings. First, recall bias may be a potential limitation as the study questionnaire was filled out by patients after CRC diagnosis and during treatment. Since questions primarily focused on patients’ previous habits, exposures, and symptoms, there is a risk that participants may not accurately recall certain events, leading to overestimation or underestimation of some reported outcomes. Additionally, selection bias could influence the findings, as patients who agreed to participate in the study may have been more motivated to share their experiences compared to those who declined participation.
Secondly, our analysis focuses exclusively on the population of CRC patients, comparing two age cohorts (EOCC and LOCC). This study does not include a comparison to the general population, which could limit the identification of differences in risk factors, habits, and exposures between CRC patients and the general population.
Lastly, while we share multidisciplinary team discussions with some participating centers and assume that all institutions generally adhere to current diagnostic and therapeutic guidelines, we cannot be certain that guideline adherence was uniform across all centers. This uncertainty may have influenced treatment consistency and patient outcomes.
Conclusion
In conclusion, EOCC patients were more likely to experience diagnostic delays and present with more advanced disease, including higher rates of metastatic disease and lymph node involvement. This highlights the need for specific screening strategies for EOCC, focusing on timely diagnosis and prevention through early endoscopy.
Acknowledgements
We would like to express our gratitude to all the participating hospitals listed above for their significant contributions and the valuable data they provided for this study.
Footnotes
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
S.E. and H. G. shared first authorship of this study.
S.T.-M. and M.v.S.u.T. shared last authorship of this study.
Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.lww.com/international-journal-of-surgery.
Contributor Information
Suna Erdem, Email: suna.erdem@clarunis.ch.
Hélène Gros, Email: helen.gros@clarunis.ch.
Jörn-Markus Gass, Email: markus.gass@luks.ch.
Anna-Katharina Huber, Email: anna-k.huber@hotmail.com.
Matthias Worni, Email: mathias.worni@hin.ch.
Mark Henschel, Email: mark.henschel@chirurgie-team-bern.ch.
Carsten T. Viehl, Email: carsten.viehl@unibas.ch.
Alexandra Müller, Email: Alexandra.Mueller@szb-chb.ch.
Urs Zingg, Email: Urs.Zingg@spital-limmattal.ch.
Daniel Stimpfle, Email: Daniel.Stimpfle@spital-limmattal.ch.
Raffaele Galli, Email: raffogalli@gmail.com.
Daniel Rodjakovic, Email: daniel.rodjakovic@outlook.com.
Mark Hartel, Email: mark.hartel@ksa.ch.
Christian Nebiker, Email: Christian.Nebiker@ksa.ch.
Thomas Simon, Email: thomas.simon@hopitalvs.ch.
Sebastian Happ, Email: Sebastian.Happ@hopitalvs.ch.
Melanie Holzgang, Email: melanie.holzgang@hin.ch.
Claudine Di Pietro Martinelli, Email: claudine.dpm@hotmail.com.
Lukas Eisner, Email: lukas.eisner@gmail.com.
Sofia Teixeira da Cunha, Email: sofia.teixeiradacunha@spital.so.ch.
Karthiga Sivalingam, Email: karthiga.sivalingam@stud.unibas.ch.
Laura Gebhardt, Email: laura.gebhardt@stud.unibas.ch.
Jennifer M. Klasen, Email: jennifer.klasen@clarunis.ch.
Ulla Friedrich, Email: friedrich.ulla@googlemail.com.
Kris Denhearynck, Email: kris.denhaerynck@unibas.ch.
Beat Müller-Stich, Email: beat.mueller@clarunis.ch.
Daniel Steinemann, Email: daniel.steinemann@clarunis.ch.
Stephanie Taha-Mehlitz, Email: stephanie.taha@clarunis.ch.
Marco von Strauss Und Torney, Email: marco.vonstrauss@clarunis.ch.
Ethical approval
Ethical approval for this study was obtained from the relevant institutional ethics committee.
Consent
Informed consent was obtained from all participants involved in the study.
Sources of funding
This study was funded by a regional cancer research organization.
Author contributions
Study concept/design: M.v.S.u.T. and S.T.-M.; data collection: S.E. and H.G.; data analysis: K.D.; Data interpretation and writing the paper: S.E. and H.G.; manuscript editing: J.M.K. and B.M.-S.; contributors assisted with data collection: J.-M.G., A.-K.H., M.W., M.H., C.T.V., A.M., U.Z., D.S., R.G., D.R., M.H., C.N., T.S., S.H., M.H., C.D.P.M., L.E., S.T.d.C., K.S., L.G., U.F.; final approval of the version to be published: M.v.S.u.T. and S.T.-M., D.S.
Conflicts of interest disclosure
The authors declare no conflicts of interest.
Research registration unique identifying number (UIN)
Not applicable.
Guarantor
Marco von Strauss und Torney and Stephanie Taha-Mehlitz.
Provenance and peer review
Not commissioned, externally peer-reviewed.
Data availability statement
Available upon reasonable request from the corresponding author.
Presentation
Preliminary results from this study were shared at a surgical conference in June 2024, during a session focused on colorectal research.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Available upon reasonable request from the corresponding author.
