Association between weight loss and survival outcomes in patients with colorectal cancer: a meta-analysis

Abstract

Background

Weight reduction is a common clinical feature observed in patients with colorectal cancer and often reflects underlying tumor burden or nutritional status. This meta-analysis aims to systematically synthesize existing evidence on the relationship between weight loss and survival outcomes in patients with colorectal cancer.

Methods

An exhaustive literature search was conducted in PubMed, Embase, and Web of Science, covering all records from the inception of each database through May 15, 2025. Inclusion criteria focused on studies reporting quantitative associations between weight loss and overall survival, progression-free survival, and colorectal cancer–specific mortality in patients with colorectal cancer. For the meta-analytic synthesis, adjusted hazard ratios (HR) with 95% confidence intervals (CI) were pooled using a random-effects model.

Results

Thirteen eligible studies involving 17,606 colorectal cancer patients were identified. Pooled estimates derived from random-effects modeling indicated that weight loss was significantly associated with shorter overall survival (HR 2.02; 95% CI 1.67–2.44) and progression-free survival (HR 1.34; 95% CI 1.14–1.58). Additionally, weight loss was linked to an increased risk of colorectal cancer–specific mortality (HR 3.27; 95% CI 1.75–6.12). Subgroup analyses revealed notably reduced overall survival among patients aged over 60 years (HR 2.94; 95% CI 2.45–3.53) and those experiencing weight loss of 10% or more (HR 3.19; 95% CI 2.58–3.93), compared to their counterparts.

Conclusions

Weight loss is a significant and independent prognostic indicator of reduced survival in patients with colorectal cancer. Further rigorous prospective studies are needed to confirm these findings and to investigate the potential underlying biological mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-025-03902-4.

Introduction

Colorectal cancer, which encompasses malignancies of both the colon and rectum, poses a significant global health challenge. With an estimated 1.9 million new cases diagnosed annually, colorectal cancer ranks as the third most prevalent cancer worldwide [1]. Despite advancements in diagnosis and treatment, it remains the second leading cause of cancer-related deaths [2]. The overall five-year survival rate for advanced colorectal cancer is relatively low [3, 4], highlighting the urgent need to identify reliable prognostic factors. Therefore, the identification of non-invasive biomarkers, such as exosomes—which have recently emerged as key players in cancer progression—is crucial for monitoring colorectal cancer progression [5]. Furthermore, specific genetic variations, including polymorphisms in leptin and leptin receptor genes, have recently been associated with colorectal cancer survival [6]. In addition to established prognostic biomarkers, the nutritional status of patients with colorectal cancer is increasingly recognized as a critical determinant of prognosis [7].

One factor that has received increasing attention as a prognostic indicator is weight loss, which is a common symptom in patients with colorectal cancer [8]. This unintentional weight loss is often attributed to factors such as dysphagia, reduced appetite, tumor-induced metabolic changes, and side effects of treatment [9]. Additionally, weight loss may also be indicative of tumor aggressiveness, systemic inflammation, or decreased tolerance to treatment [10]. While previous studies have examined the impact of weight loss on survival outcomes in colorectal cancer, the reported results have been inconsistent [11–16]. These discrepancies may be due to variations in study design, population characteristics, tumor histology, or definitions and measurements of weight loss.

The prognostic value of weight loss has been well established in other types of cancer, such as lung [17] and gastric [18] cancers. However, the specific impact of weight loss on survival outcomes in colorectal cancer patients has not been quantitatively synthesized through meta-analysis. To address this gap, we conducted a meta-analysis to evaluate the association between weight loss and survival outcomes in patients with colorectal cancer, specifically in terms of overall survival, progression-free survival (PFS), and colorectal cancer specific-mortality (CCSM).

Materials and methods

Search strategy

The current study followed the established guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [19]. A thorough search of published literature was conducted using PubMed, Embase, and Web of Science, covering records from the earliest available to May 15, 2025. The search strategy utilized a combination of keywords related to “weight loss”, “colorectal cancer”, and “survival”. The detailed search is presented in Supplemental Text S1. We limited our analysis to articles published in English. Additionally, we manually reviewed the reference lists of relevant reviews and eligible studies to identify any additional relevant publications.

Study selection

The study selection process involved two independent reviewers who screened titles and abstracts, obtained potentially relevant full-text articles, and assessed them for eligibility based on the pre-specified inclusion criteria. In cases of disagreement, a third reviewer was consulted to resolve any discrepancies. The eligible studies had to meet the following criteria: (1) Patients with a diagnosis of colorectal cancer; (2) Weight loss calculated as a percentage of weight reduction; (3) Patients with relatively stable weight (within a cutoff degree of ± weight loss) as comparators; (4) Overall survival, PFS, CCSM as outcomes of interest; (5) Retrospective or prospective observational as study design; and (6) Availability of adjusted hazard ratios (HR) and 95% confidence intervals (CI) related to weight reduction and the aforementioned outcomes. In case where studies included overlapping participant groups, we prioritized the publication with the most comprehensive dataset for inclusion. The following exclusion criteria were applied: (1) Weight reduction reported solely as changes in body mass index (BMI) or kilograms; (2) Absence of clear definition of weight reduction; (3) Relative risk based exclusively on unadjusted survival analysis; and (4) Short-term outcomes defined as in-hospital or 30-day results.

Data extraction and quality assessment

Two authors independently conducted data extraction using a pre-designed standardized form. The extracted information comprised: study characteristics (first author’s surname, publication year, study region, design type, number of patients, intervention details, and follow-up time), patient demographic characteristics (median or mean age, sex distribution, and cancer stage), weight loss definitions (degree of weight reduction and timing of determination), and survival endpoints (maximum adjusted HR with 95% CI, along with covariates included in multivariate models). To ensure the quality of the studies, two reviewers independently applied the Newcastle-Ottawa Scale (NOS) for cohort studies [20]. This tool assesses three domains: participant selection, group comparability, and outcome assessment. Studies were categorized as high quality (NOS score ≥ 7) or moderate quality (NOS scores 4–6). In cases where discrepancies arose between the reviewers, they were resolved through consultation and discussion until a consensus was achieved.

Data analysis

Stata version 12.0 (StataCorp, College Station, TX) was used for all statistical analyses. The association between weight loss and survival outcomes was quantified using pooled adjusted HR and 95% CI. Heterogeneity across studies was evaluated using both the I² statistic and Cochran’s Q test. Significant heterogeneity was defined as an I² value exceeding 50% or a p-value less than 0.10 for Cochran’s Q test. A random-effects model was selected for all analyses to account for potential clinical heterogeneity. We conducted pre-specified subgroup analyses based on factors known to influence survival outcomes: study design (retrospective versus prospective), geographic region (Europe versus America), patients’ number (>1000 versus ≤ 1000), age group (>60 versus ≤ 60 years), cancer subtype (colon cancer versus metastatic colorectal cancer versus all colorectal cancer), weight loss measure (medical records versus patient self-report versus actual measure), timing of weight loss measurement (unclear versus post-diagnosis), degree of weight loss (≥ 5% versus ≥ 10%), and duration of follow-up (>24 versus ≤ 24 months). To assess the robustness of the findings, we conducted sensitivity analyses by iteratively excluding one study at a time. Publication bias was assessed using Begg’s test [21], Egger’s test [22], and visual inspection of funnel plots.

Results

Search results

A systematic search across medical databases initially yielded 613 records. Following duplicate removal, 303 unique publications advanced to the title and abstract screening, 263 articles were removed based on obvious irrelevance to the topic, and then 40 articles were retrieved for full-text assessment. After applying pre-defined inclusion and exclusion criteria, 13 studies [11–16, 23–29] were selected for inclusion in the meta-analysis. The detailed study selection process is illustrated in Fig. 1.

Fig. 1.

Study selection process flow diagram

Study characteristics

Table 1 presents the key characteristics of the studies included in this analysis. These studies were published between 2004 and 2022 and were conducted in various geographic regions, including the United States [16, 23–25], Canada [13], France [11], Germany [28], Greece [12], Spain [29], and China [26]. The study designs were predominantly retrospective, with only three studies [14, 25, 29] applying a prospective design. The sample sizes varied greatly, ranging from 149 to 3,504 individuals, with a total of 17,606 colorectal cancer patients. Weight loss was defined as a reduction in body weight of more than 5.0% or 10%. The prevalence of weight loss varied from 12.6% to 65.6%. The timing of weight loss assessment also varied, with measurements taken at diagnosis or during the course of treatment. The median follow-up duration ranged from 6 months to 5.1 years. Based on the NOS criteria, the majority of studies were classified as high quality, with only three studies [11, 12, 24] deemed to be of moderate quality(Supplemental Table S1).

Table 1.

Main characteristics of the included studies

Author/year	Region	Study design	Patients (% men)	Age (years)	Tumor stage	WL measure	Treatment	WL definition	Reference weight	Outcomes/ HR (95% CI)	Follow-up	Adjusted variables
Mitry 2004 [11]	France	R	mCRC 602 (59.5)	NP	IV	NP	CT	WL ≥ 5% (18.8)	< 5%	OS 1.67 (1.29–2.14) PFS 1.25 (1.00–1.58.00.58)	NP	PS, metastatic sites, alkaline phosphatase, irinotecan-containing regimen
Zacharakis 2010 [12]	Greece	R	mCRC 541 (55.1)	Mean 60.3	IV	Medical records	CT	WL ≥ 10% (38.3)	< 10%	OS 3.32 (2.62–4.20)	NP	PS, chemotherapy, Hb, anorexia, fatigue, albumin, CRP, blood transfusions, skin complications
Vergidis 2016 [13]	Canada	R	CC 539 (52)	Median 69	III	Actual measure	CT	WL ≥ 5% at post-diagnosis (12.6)	< 5%	OS 1.92 (1.00–3.70.00.70)	4.9 years	Age, sex, PS, baseline BMI
Kocarnik 2017 [14]	Multination	P	CRC 2049 (50)	Mean 54.8	I–IV	Patient self-report	CT, RT	WL > 5% at 5 years post diagnosis (19)	< 5%	OS 2.58 (1.97–3.38) CCSM 4.31(2.63–7.06)	5.1 years	Age, sex,, NSAID use, stage at diagnosis, time from diagnosis to survey, BMI, study
Meyerhardt 2017 [23]	USA	R	CRC 2781 (49.6)	Median ≥ 62	I–III	Actual measure	CRT	WL > 5% post diagnosis (21.1%)	< 5%	OS 2.39 (1.29–4.43)# CCSM 2.26 (1.13–4.51)#	50 months	Age, sex, baseline weight, race/ethnicity, cancer stage, grade, chemotherapy, radiotherapy cancer site
Islam 2020 [24]	USA	R	Metastatic CC 149 (52)	Mean 63.5	NP	Medical records	TT	Unexplained WL > 10% (32.1)	≤ 10%	OS 2.73(1.73–4.31)	19.4 months	Disease progression
Lee 2020 [15]	Multination	R	CC 3449 (51.2)	NP	II–III	Actual measure	CT, surgery	WL ≥ 5% during first 6 month of CT (10.2)	< 5%	OS 1.14 (0.79–1.65)#	37.8 month	Age, sex, cancer stage, PS, chemotherapy, BMI, smoking
Guercio 2020 [25]	USA	P	mCRC 2323 (58.3)	Median < 59.7	IV	Patient self-report	CT, TT	WL > 5% prior 6 months (65.6)	< 5%	OS 1.33(1.13–1.56)# PFS 1.15 (1.01–1.31)#	5.98 years	Age, sex, PS, chemotherapy, adjuvant chemotherapy, or radiation therapy, treatment arm, KRAS, primary tumor site, PA, comorbidity
Hu 2021 [26]	China	R	CRC 902 (58.4)	Mean 53.7	II–III	Medical records	Surgery/CT	WL ≥ 5% at 6 months after surgery (NP)	˂ 5%	OS 2.56(2.0–3.23.0.23)	> 35 months	Multivariable adjusted model
Best 2021 [16]	USA	R	mCRC 226 (53)	Median 59	IV	Medical records	CT, TT	WL ≥ 5% at 3 months post diagnosis (22)	< 5%	OS 2.10 (0.84–5.24)	57 months	Age, sex, mutation, baseline skeletal muscle or weight values
Franko 2022 [27]	Multination	R	mCRC 3504 (59.3)	NP	IV	Actual measure	TT	WL ≥ 5% at 3 months post diagnosis (19.7)	Gain/stable	OS 1.87 (1.67–2.10) PFS 1.48 (1.31–1.68)	NP	Age, sex, BMI, PS, number of metastatic sites, targeted treatment type
Liu 2022 [28]	Germany	R	mCRC 326 (72.4)	NP	IV	Medical records	ST	WL ≥ 5% at 3 months post diagnosis (14.4)	< 5%	OS 1.64(1.13–2.38) PFS 1.72 (1.18–2.50)	9–11.8.8 months	Age, sex, PS, liver limited disease, CEA, primary tumor site, number of metastatic sites, treatment
Feliu 2022 [29]	Spain	P	CRC 215 (58)	Median 78	I–IV	Patient self-report	CT	WL > 5% at 6 months prior CT (34%)	≤ 5%	OS 2.54 (1.24–5.11)	6 months	Tumor stage, Hb, Activity of Daily Living

Overall survival

All the included studies examined the association between weight loss and overall survival outcome. Meta-analysis indicated a significant association between weight loss and reduced overall survival (pooled HR 2.02; 95% CI 1.67–2.44; Fig. 2). However, substantial heterogeneity was observed among the studies (I² = 81.2%; p < 0.001). A sensitivity analysis was conducted and found that removing any single study did not change the primary statistical significance of the results. Subgroup analyses also supported the consistency of this association, with significant findings across different study designs, geographic regions, sample sizes, colorectal cancer subtypes, patient age groups, weight loss assessment, and follow-up durations (Table 2). No evidence of publication bias was detected, as indicated by the funnel plots (Fig. 3), Begg’s test (p = 0.951), and Egger’s test (p = 0.480).

Fig. 2.

Pooled adjusted HR with 95% CI for overall survival comparing weight loss versus relatively stable weight

Table 2.

Subgroup analysis on overall survival

Subgroups	No. of studies	Pooled adjusted HR	95% CI	Heterogeneity between studies
Study design
Prospective	3	1.98	1.16–3.40	p < 0.001; I2 = 89.3%
Retrospective	10	2.05	1.67–2.51	p < 0.001; I2 = 75.8%
Geographical region
America	4	2.18	1.43–3.32	p < 0.001; I2 = 83.9%
Europe	5	2.11	1.41–3.17	p < 0.001; I2 = 83.0%
Number of patients
> 1000	5	1.73	1.33–2.26	p < 0.001; I2 = 84.9%
≤ 1000	8	2.28	1.81–2.87	p = 0.005; I2 = 65.3%
Cancer subtypes
mCRC	7	1.96	1.52–2.53	p < 0.001; I2 = 86.2%
All colorectal cancer	6	2.10	1.56–2.82	p = 0.008; I2 = 67.8%
Baseline age
>60 years	5	2.94	2.45–3.53	p = 0.501; I2 = 0.0%
≤ 60 years	4	2.05	1.33–3.17	p < 0.001; I2 = 89.6%
Weight loss measurement
Medical records	5	2.51	1.94–3.24	p = 0.037; I2 = 60.9%
Patient self-report	3	1.98	1.16–3.40	p < 0.001; I2 = 89.3%
Actual measure	4	1.71	1.27–2.29	p = 0.066; I2 = 58.2%
Timing of weight loss measure
Pre-diagnosis	10	1.88	1.54–2.29	p < 0.001; I2 = 75.7%
Unclear	3	2.46	1.53–3.97	p < 0.001; I2 = 87.0%
Degree of weight loss
≥ 5%	11	1.85	1.55–2.20	p < 0.001; I2 = 73.3%
≥ 10%	2	3.19	2.58–3.93	p = 0.455; I2 = 0.0%
Follow-up duration
>24 months	7	1.89	1.38–2.59	p < 0.001; I2 = 82.9%
≤ 24 months	3	2.15	1.50–3.07	p = 0.199; I2 = 38.2%

HR hazard ratios, CI confidence intervals, mCRC metastatic colorectal cancer

Fig. 3.

Funnel plot analysis of publication bias for overall survival

Progression -free survival and colorectal cancer specific-mortality

Four studies [11, 25, 27, 28] evaluated the impact of weight loss on PFS, while two studies [14, 23] assessed its association with CCSM. Meta-analysis revealed that weight loss significantly correlated with reduced PFS (pooled HR 1.34; 95% CI 1.14–1.58; Fig. 4A), although there was considerable heterogeneity (I² = 69.1%; p = 0.021). Sensitivity analyses confirmed the stability of this association, as excluding individual studies one by one did not significantly change the original pooled estimate. Similarly, pooled data from two studies demonstrated a strong link between weight loss and an increased risk of CCSM (HR 3.27; 95% CI 1.75–6.12; Fig. 4B), with moderate heterogeneity (I² = 54.9%; p = 0.137).

Fig. 4.

Pooled adjusted HR with 95% CI for progression-free survival (A) and colorectal cancer specific-mortality (B) comparing weight loss versus relatively stable weight

Discussion

The current meta-analysis of 13 studies involving 17,606 colorectal cancer patients provides compelling evidence that weight loss is significantly associated with reduced overall survival. The pooled analysis indicated that colorectal cancer patients who experienced weight loss had a 2.02-fold decrease in overall survival. Furthermore, the pooled risk estimates of 1.34 for PFS and 3.27 for CCSM underscore the importance of considering weight loss as a critical prognostic factor in the management of colorectal cancer.

Our subgroup analyses identified populations at exceptionally high risk, specifically patients older than 60 years and those experiencing weight loss exceeding 10%. The significant impact on older patients may be attributed to an accelerated decline in muscle mass and physiological reserve, which is a synergistic interaction between cancer cachexia and age-related sarcopenia [30]. Meanwhile, the extreme hazard observed in the ≥ 10% weight loss group likely reflects an advanced, hypermetabolic cachectic state driven by intense systemic inflammation [31]. These findings underscore that weight loss is not a uniform risk factor and that tailored interventions for these specific high-risk subgroups are critically needed. Furthermore, the strength of the association between weight loss and overall survival varied depending on the method of measurement. The strongest risk was identified through medical record review (HR 2.51), followed by patient self-report (HR 1.98), while a weaker effect was observed with actual measurement (HR 1.71). This gradient suggests that less objective methods may exaggerate the apparent strength of the relationship due to potential recall bias.

Beyond evaluating weight loss as a percentage of total body weight reduction, several studies have also examined its prognostic significance in changes in body mass index (BMI) among patients with colorectal cancer. Walter et al. reported that a prediagnostic decrease in BMI of 5 kg/m² was independently associated with a significant reduction in overall survival (HR 1.93), CCSM (HR 1.99), recurrence-free survival (HR 1.83), and disease-free survival (HR 1.80) in 3,130 colorectal cancer patients [32]. Lin et al. indicated that a BMI loss of 7% or more during preoperative chemoradiotherapy was associated with a 1.98-fold decrease in overall survival in patients with locally advanced rectal cancer [33]. Furthermore, metastatic colorectal cancer patients who experienced weight loss exceeding 0.05% per week had shorter PFS during first-line treatment [34]. These findings, which align with the percentage of weight loss observed, further support the notion that weight reduction serves as an adverse prognostic indicator for poorer survival outcomes in colorectal cancer patients.

Significant heterogeneity was observed in the analyses of overall survival and PFS. This heterogeneity may be attributed to variations in study design, patient demographics, colorectal cancer subtypes, cancer stages, methods of assessing weight loss, degree of weight loss, and follow-up duration. Although subgroup analyses based on these factors reduced heterogeneity to some extent, significant heterogeneity persisted in certain subgroups. Specifically, the diversity of anti-cancer treatments may also contribute to the observed variability. Unfortunately, further subgroup analyses could not be conducted due to insufficient data in the included studies.

The observed association between weight loss and survival outcomes in colorectal cancer is multifactorial and warrants further investigation into its underlying biological mechanisms. Cancer cachexia, a complex metabolic syndrome characterized by the involuntary loss of lean body mass and fat, is a significant contributor [35]. This syndrome is often exacerbated by the tumor’s inflammatory stimuli [36]. Systemic inflammation, a hallmark of advanced cancer, plays a pivotal role in mediating the adverse effects of weight loss [37]. This chronic inflammatory state also creates a microenvironment that can promote tumor growth and metastasis [38]. Notably, the nutritional status of colorectal cancer patients is profoundly affected by weight loss. This can result from reduced food intake due to anorexia or treatment-related side effects, impaired nutrient absorption caused by tumor location or gastrointestinal dysfunction, and increased nutrient demands from the tumor. Nutritional deficiencies can weaken the immune response, decrease tolerance to anticancer therapies, and worsen treatment-related side effects [39]. Beyond these factors, the gut microbiota is another critical factor to consider [40]. Dysbiosis, common in colorectal cancer, can impair nutrient absorption and promote a pro-inflammatory state, potentially exacerbating cachexia and negatively impacting survival outcomes [41].

Our meta-analysis indicates that weight loss may serve as a valuable tool for risk stratification in colorectal cancer. Incorporating weight reduction into existing prognostic models could help identify high-risk patients who may benefit from more intensive interventions. Clinically, this approach entails careful monitoring of patient weight changes, along with timely referrals to tailored nutritional interventions upon reaching a clinically significant threshold of weight decline. However, prospective studies using standardized definitions of weight loss and rigorous control of confounding factors are essential to confirm these associations and establish optimal intervention thresholds. Furthermore, well-designed clinical trials are necessary to evaluate the effectiveness of targeted nutritional strategies in mitigating the adverse effects of weight loss on survival outcomes.

Several limitations must be acknowledged in this meta-analysis. First, the majority of the included studies were retrospective observational designs, which limit the ability to establish a causal relationship between weight loss and reduced survival. Second, a significant limitation stems from the lack of standardized protocols for measuring weight loss. Variations in the definitions of weight loss—specifically differences in the assessment time frame and the threshold for clinically significant weight change—may impede direct comparability of the reported results. Third, substantial heterogeneity was observed in the analyses of overall survival and PFS. Finally, the prognostic significance of weight loss in colorectal cancer may be influenced by baseline body weight, potentially obscuring the true association due to the obesity paradox. Additionally, confounding factors such as cancer stage, performance status, and treatment received may have affected the observed associations. The absence of adjustments for these potential confounders may have introduced bias into the pooled risk estimates, potentially leading to overestimation or underestimation of the true association.

Conclusions

Weight loss is a significant and independent prognostic factor associated with reduced survival in patients with colorectal cancer. Clinicians should closely monitor weight changes in these patients and consider appropriate nutritional interventions to mitigate the adverse effects of weight loss on survival. Future prospective studies are needed to validate these findings and to establish the optimal threshold for defining clinically significant weight loss in this population.

Abbreviations

HR

Hazard ratio

CI

Confidence intervals

NP

Not provided

R

Retrospective

P

Prospective

CC

Colon cancer

CRC

Colorectal cancer

mCRC

Metastatic colorectal cancer

CT

Chemotherapy

WL

Weight loss

OS

Overall survival

RT

Radiotherapy

CT

Chemotherapy

CRT

Chemoradiotherapy

ST

Systemic treatment

TT

Target therapy

Hb

Hemoglobin

BMI

Body mass index

OS

Overall survival

PFS

Progressionfree survival

CCSM

Colorectal cancer specificmortality

PS

Performance status

CRP

Creactive protein

CEA

Carcinoembryonic antigen

NSAID

Non-steroidal anti-inflammatory drug

PA

Physical activity

KRAS

Kirsten Rat Sarcoma Viral Oncogene Homolog

Author contributions

FY contributed to study conception/design and interpretation of data. WGF and LZY contributed to literature search, data extraction, quality assessment. GDD and MCF contributed to statistical analysis. LZY drafted the manuscript. WGF revised the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by (1) Key project fund of Jiangsu Provincial Health Commission (K2023016); (2) Social Development Fund of Zhenjiang (SH2024002).

Data availability

All data generated are included in this published article and its additional files.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.