Weight Loss, Obesity Medication, and Risk of Obesity‐Associated Cancer: A Meta‐Analysis of Randomized Controlled Trials

Chengwen Li; Chu Lin; Xiaoling Cai; Fang Lv; Wenjia Yang; Linong Ji

doi:10.1002/oby.70054

. 2025 Nov 4;34(Suppl 2):16–24. doi: 10.1002/oby.70054

Weight Loss, Obesity Medication, and Risk of Obesity‐Associated Cancer: A Meta‐Analysis of Randomized Controlled Trials

Chengwen Li ¹, Chu Lin ¹, Xiaoling Cai ^1,^✉, Fang Lv ¹, Wenjia Yang ¹, Linong Ji ^1,^✉

PMCID: PMC13535721 PMID: 41189318

ABSTRACT

Objective

This study aimed to determine whether weight reduction mediated by antiobesity medications (AOMs) contributes to the risk reduction in obesity‐associated cancer.

Methods

PubMed, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, and the ClinicalTrials.gov website were systematically searched for randomized controlled trials of AOMs from inception to December 2024. Relative risks were calculated using a random‐effects model.

Results

The analysis included 25 randomized controlled trials with 40,731 participants. Compared with placebo, AOMs showed no association with the risk of overall obesity‐related cancer (RR = 1.03, 95% CI: 0.78 to 1.37) or site‐specific cancer. Consistently, every 5 kg weight reduction mediated by AOMs was not associated with the risk of overall obesity‐related cancer (RR = 0.97, 95% CI: 0.84 to 1.12) or site‐specific cancer. However, subgroup analysis revealed that coagonists (tirzepatide, cotadutide, and cagrilintide) significantly reduced overall obesity‐associated cancer risk (RR = 0.43, 95% CI: 0.19 to 0.97), and every 5 kg weight reduction mediated by coagonists was marginally associated with a reduced overall obesity‐associated cancer risk (RR = 0.79, 95% CI: 0.62 to 1.00).

Conclusions

Weight reduction mediated by current AOMs was not associated with a reduced risk of overall or site‐specific obesity‐associated cancer in patients with overweight or obesity, while a decreased risk of overall obesity‐associated cancer was observed in coagonist users.

Keywords: meta‐analysis, obesity medication, obesity‐associated cancer, weight loss

Study Importance.

What is already known?
- ○
  Obesity is an established independent risk factor for multiple cancers.
- ○
  Prior evidence on whether antiobesity medications (AOMs) reduce the risk of obesity‐related cancer has been inconsistent.
What does this review add?
- ○
  Weight loss mediated by most AOMs showed no significant association with reduced overall or site‐specific risk of obesity‐related cancer.
- ○
  Coagonists (e.g., tirzepatide) uniquely demonstrated a statistically significant reduction in the overall risk of obesity‐related cancer.
How might these results change the direction of research or the focus of clinical practice?
- ○
  Weight reduction mediated by AOMs might not be sufficient to modify the risk of obesity‐related cancer.

1. Introduction

Obesity is a critical global health concern, linked to various chronic diseases, such as cardiovascular diseases, type 2 diabetes, and cancer [1]. Numerous studies have confirmed that obesity is an independent risk factor for multiple types of cancer, emphasizing the need to address it in cancer prevention strategies [2]. The mechanisms through which obesity facilitates cancer development are intricate and multifaceted. Excess adipose tissue can lead to chronic low‐grade inflammation, creating a protumorigenic microenvironment [3]. Moreover, obesity is associated with hormonal imbalances, such as increased levels of estrogen and insulin‐like growth factor‐1 (IGF‐1), which can promote cell proliferation and inhibit apoptosis, thereby facilitating tumor growth [4]. Additionally, obesity‐induced insulin resistance can lead to hyperinsulinemia, which may stimulate cancer cell growth through the activation of insulin receptors and downstream signaling pathways [5].

Given the established connection between obesity and cancer, weight reduction has been proposed as a potential strategy to mitigate this risk. While lifestyle modifications like dietary changes and increased physical activity are traditionally recommended, their long‐term efficacy in achieving significant weight loss is often limited [6]. In recent years, the development of antiobesity medications (AOMs) has offered a promising alternative for weight reduction. These medications target various physiological processes involved in appetite regulation, energy expenditure, and fat absorption, thereby promoting weight loss. For instance, orlistat works by inhibiting dietary fat absorption, while others, like the glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs), enhance satiety and reduce food intake by mimicking the effects of the gut hormone GLP‐1 [7].

The potential impact of AOMs on cancer risk has garnered considerable attention. Theoretically, weight loss through AOMs could reduce cancer risk by alleviating obesity‐related inflammation, hormonal imbalances, and insulin resistance. However, concerns have been raised regarding the potential adverse effects of AOMs on cancer incidence, with some studies suggesting direct or indirect effects on cancer cells [8]. The evidence regarding the association between AOMs and cancer risk remains inconclusive, with several meta‐analyses showing inconsistent results. Some studies reported a reduced risk of specific cancers, such as colorectal cancer and breast cancer, in individuals using AOMs, while others found no significant association or even an increased risk of certain cancer types [9, 10, 11, 12].

This uncertainty highlighted the need for a comprehensive and up‐to‐date meta‐analysis to clarify the relationship between AOMs and obesity‐associated cancer risk. The primary objective of this study was to assess the association between AOM treatments and the risk of prespecified obesity‐associated cancer in patients with overweight or obesity. By analyzing the obesity‐related cancer outcomes from randomized controlled trials (RCTs) reporting significant weight reductions, we aimed to clarify this association and provide insights for clinical decision‐making regarding AOMs in obesity management. Different from previous studies that evaluated the associations between GLP‐1RAs and cancer risks [10, 13], our meta‐analysis evaluated all AOMs indicated for weight loss, not merely GLP‐1RAs, including glucose‐dependent insulinotropic polypeptide (GIP)/GLP‐1 or glucagon (GCG)/GLP‐1 coagonists and even triagonists. To note, drugs not approved for weight loss were excluded, even if they fell into these drug classes. Moreover, we quantified how graded weight loss (per 5 kg reduction) related to site‐specific cancer risk, which was not well understood previously.

2. Methods

2.1. Study Design and Registration

This systematic review and meta‐analysis was conducted according to the guidelines of Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) protocol. It has been registered in International Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD42024610552.

2.2. Data Sources and Searches

Two independent investigators conducted systematic searches of PubMed, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, and ClinicalTrials.gov website for studies published from inception to December 2024. The search terms were as follows: overweight; obesity; cancer; tumor; neoplasm; placebo‐controlled; RCTs. With these terms, the following AOMs were searched respectively: liraglutide, semaglutide, orlistat, benaglutide, orforglipron, mazdutide, survodutide, maritide, bimagrumab, tirzepatide, cotadutide, cagrilintide, retatrutide, phentermine plus topiramate, and naltrexone plus bupropion. The full search strategy is summarized in Table S1.

2.3. Data Selection and Inclusion

The inclusion criteria for this meta‐analysis were as follows: (1) RCTs of different AOMs; (2) studies reporting predefined obesity‐associated cancer outcomes; (3) placebo‐controlled studies; (4) publications in English. The exclusion criteria for this meta‐analysis were as follows: (1) studies not conducted in patients with overweight or obesity; (2) studies using drugs not approved for weight loss or doses of approved drugs outside their licensed weight loss indication; (3) studies without a significant weight change difference during the follow‐up duration.

2.4. Definition of the Cancer Outcome

Based on previous studies, obesity may increase the risk of certain cancers, which are defined as obesity‐related cancers, including esophageal cancer, breast cancer, colorectal cancer, endometrial cancer, gallbladder cancer, stomach cancer, kidney cancer, hepatocellular cancer, ovarian cancer, pancreatic cancer, thyroid cancer, meningioma, and multiple myeloma [10]. Our study defined these cancers as the obesity‐related cancer endpoints for this meta‐analysis.

2.5. Data Extraction and Quality Evaluation

According to the inclusion and exclusion criteria, study data were independently extracted from eligible RCTs by two investigators (Chengwen Li and Chu Lin), including first author, publication year, study design, number of participants, age, sex ratio, follow‐up duration, type 2 diabetes status, drug exposure (types of AOMs), weight at baseline, weight after treatment, baseline body mass index (BMI), and predefined obesity‐related cancer events. If data on certain obesity‐related cancer events were unavailable in both original articles and supplementary materials, required data would be retrieved from the ClinicalTrials.gov website with the unique registered NCT number. The investigators jointly double‐checked the accuracy of the data. Any disagreements upon data extraction were resolved by discussion with a third investigator (Xiaoling Cai).

2.6. Data Synthesis and Analysis

For data synthesis and analysis, we collected the means and standard deviations (SDs) of weight changes following the use of AOMs for each included study. The weighted mean differences (WMD) and 95% confidence intervals (CI) for weight change from baseline were computed using Stata software (version 18.0; StataCorp LLC) and Review Manager software (version 5.3; Nordic Cochrane Centre, Copenhagen, Denmark). The relative risk (RR) and 95% CI for obesity‐associated cancer incidence were calculated using the Mantel–Haenszel random‐effects model. Statistical significance was considered at p < 0.05.

To further explore potential influences on outcomes, we conducted subgroup analyses based on various baseline characteristics, including age, sex ratio, BMI, follow‐up duration, type 2 diabetes status (with/without), and types of AOMs.

The quality of the included RCTs was assessed by two independent authors (Chengwen Li and Chu Lin) using the Cochrane Collaboration risk of bias (RoB) tool, including selection bias, performance bias, detection bias, and reporting bias.

3. Results

3.1. Characteristics and Quality Assessment of Included Studies

As shown in Figure 1, 25 RCTs were included, involving 23,877 participants in the experimental group and 16,854 participants in the control group in this meta‐analysis. The mean age of all participants was 54.2 ± 7.6 years old; the mean male percentage was 51.3% ± 22.7%; the mean BMI was 35.3 ± 2.1 kg/m²; the mean body weight at baseline was 100.1 ± 4.5 kg, and the mean follow‐up duration was 65.2 ± 26.7 weeks. There were 25.0% patients with type 2 diabetes and 75.0% without. The detailed baseline characteristics of the included studies are systematically summarized in Table S2.

PRISMA flow diagram of included studies.

The predefined obesity‐associated cancers included esophageal, breast, colorectal, endometrial, stomach, kidney, hepatocellular, ovarian, pancreatic, and thyroid cancers, as well as meningioma and multiple myeloma (gallbladder cancer was excluded due to no reported events). There were 13 trials investigating GLP‐1RAs, 4 trials investigating GLP‐1 and GIP receptor coagonist (tirzepatide), 1 trial investigating GLP‐1 and GCG receptor coagonist (cotadutide), 1 trial investigating amylin and calcitonin receptor coagonist (cagrilintide), 1 trial investigating GLP‐1, GIP, and glucagon receptor triagonist (retatrutide), 2 trials investigating phentermine/topiramate, and 3 trials investigating naltrexone/bupropion.

The risk of bias was evaluated using the Cochrane RoB 2 tool, which showed that all 25 included RCTs demonstrated a low risk of bias in domains D1 (Bias arising from the randomization process), D2 (Bias due to deviations from intended interventions), D4 (Bias in measurement of the outcome), and D5 (Bias in selection of the reported result). However, three trials [14, 15, 16] showed a high risk of bias due to missing outcome data (domain D3) (Table S3 and Figure S1).

3.2. The Association Between AOM Treatments and the Risk of Obesity‐Associated Cancer

Compared with placebo, the AOM treatments were not associated with a reduced risk of overall obesity‐associated cancer (RR = 1.03, 95% CI: 0.78 to 1.37). Similarly, the AOM treatments were not associated with the risk of each site‐specific obesity‐associated cancer, including esophageal cancer (RR = 0.77, 95% CI: 0.13 to 4.68), breast cancer (RR = 0.67, 95% CI: 0.33 to 1.28), colorectal cancer (RR = 0.98, 95% CI: 0.61 to 1.57), endometrial cancer (RR = 0.65, 95% CI: 0.22 to 1.88), stomach cancer (RR = 1.20, 95% CI: 0.37 to 3.93), kidney cancer (RR = 0.96, 95% CI: 0.19 to 4.72), hepatocellular cancer (RR = 1.32, 95% CI: 0.50 to 3.47), ovarian cancer (RR = 1.23, 95% CI: 0.12 to 12.37), pancreatic cancer (RR = 0.60, 95% CI: 0.17 to 2.05), thyroid cancer (RR = 1.42, 95% CI: 0.59 to 3.42), meningioma (RR = 1.16, 95% CI: 0.21 to 6.35), and multiple myeloma (RR = 0.81, 95% CI: 0.28 to 2.41) (Figure 2).

The association between obesity medication and the risk of overall and site‐specific obesity‐associated cancers in patients with overweight and obesity. Relative risk (RR) and 95% CI for: (a) overall predefined obesity‐associated cancer, (b) site‐specific cancer, and (c) subgroup analysis stratified by drug types. BUP, bupropion; GLP‐1RA, glucagon‐like peptide‐1 receptor agonist; NAL, naltrexone; PHEM, phentermine; TPM, topiramate.

However, subgroup analyses revealed a significant association between treatment with coagonists (tirzepatide, cotadutide, and cagrilintide) and the risk reduction of overall cancer events (RR = 0.43, 95% CI: 0.19 to 0.97), while no significant associations were found between overall cancer and other AOMs, including GLP‐1RAs, triagonists, phentermine‐topiramate, and naltrexone‐bupropion (Figure 2).

3.3. The Effect of a 5 kg Body Weight Reduction Mediated by AOMs on the Risk of Obesity‐Associated Cancer

When compared with placebo, every 5 kg weight reduction mediated by AOMs was not associated with a decreased risk of overall obesity‐associated cancer (RR = 0.97, 95% CI: 0.84 to 1.12). Similarly, every 5 kg weight reduction mediated by AOMs was not associated with a decreased risk of each prespecified obesity‐associated cancer, including esophageal cancer (RR = 0.82, 95% CI: 0.19 to 3.61), breast cancer (RR = 0.83, 95% CI: 0.61 to 1.15), colorectal cancer (RR = 0.94, 95% CI: 0.72 to 1.24), endometrial cancer (RR = 0.87, 95% CI: 0.54 to 2.30), stomach cancer (RR = 1.12, 95% CI: 0.54 to 2.30), kidney cancer (RR = 0.95, 95% CI: 0.61 to 1.48), hepatocellular cancer (RR = 1.24, 95% CI: 0.67 to 2.32), ovarian cancer (RR = 1.05, 95% CI: 0.34 to 3.20), pancreatic cancer (RR = 0.67, 95% CI: 0.35 to 1.27), thyroid cancer (RR = 1.10, 95% CI: 0.76 to 1.59), meningioma (RR = 0.98, 95% CI: 0.55 to 1.74), and multiple myeloma (RR = 0.79, 95% CI: 0.28 to 2.41) (Figure 3).

Standardized effect of every 5 kg body weight change on the risk of overall and site‐specific obesity‐associated cancer mediated by obesity medications compared with placebo in patients with overweight and obesity. Relative risk (RR) and 95% CI for: (a) overall predefined obesity‐associated cancer, (b) site‐specific cancer, and (c) subgroup analysis stratified by age, BMI, male percentage, follow‐up duration, diabetes status, and drug types. BUP, bupropion; GLP‐1RA, glucagon‐like peptide‐1 receptor agonist; NAL, naltrexone; PHEM, phentermine; TPM, topiramate.

In our subgroup analyses, no significant associations were found in patients stratified by age (over 60 years: RR = 1.07, 95% CI: 0.86 to 1.33; under 60 years: RR = 0.89, 95% CI: 0.73 to 1.08), baseline BMI (over 35 kg/m²: RR = 0.87, 95% CI: 0.71 to 1.07; under 35 kg/m²: RR = 1.06, 95% CI: 0.86 to 1.31), sex proportion (male > 50%: RR = 1.07, 95% CI: 0.87 to 1.32; male < 50%: RR = 0.88, 95% CI: 0.72 to 1.08), follow‐up duration (over 52 weeks: RR = 0.97, 95% CI: 0.83 to 1.12; under 52 weeks: RR = 1.00, 95% CI: 0.47 to 2.14), or diabetes status (diabetes: RR = 0.92, 95% CI: 0.61 to 1.38; no diabetes: RR = 0.98, 95% CI: 0.83 to 1.14). However, in the drug type subgroup, an exception was observed in patients treated with coagonists (tirzepatide, cotadutide, and cagrilintide), where a 5 kg weight reduction was associated with a marginally significant reduction in overall cancer risk (RR = 0.79, 95% CI: 0.62 to 1.00), while there were no significant associations between overall cancer and other AOMs, including GLP‐1RAs, triagonists, phentermine‐topiramate, and naltrexone‐bupropion (Figure 3).

3.4. Meta‐Regression Analysis Outcomes

This meta‐regression analysis revealed that the absolute weight loss mediated by AOMs was not associated with the relative risk of overall obesity‐related cancer (β = −1.61, 95% CI, −4.80 to 1.58, p = 0.31) and other site‐specific cancers. Meanwhile, the weight reduction difference between AOM and placebo groups was not associated with a reduced risk of overall cancer (β = −1.51, 95% CI: −3.94 to 0.92, p = 0.21) or other site‐specific cancers (Tables S4, S5 and Figures S11, S12).

4. Discussion

Our meta‐analysis revealed that among current AOMs, weight reduction achieved through most types of them was not significantly associated with a reduced risk of overall obesity‐related cancer. This absence of association was consistent across various cancer types, including esophageal, breast, colorectal, endometrial, stomach, kidney, hepatocellular, ovarian, pancreatic, and thyroid cancer, as well as meningioma and multiple myeloma. Notably, subgroup analysis identified an exception that the use of coagonists was associated with a reduced risk of overall obesity‐related cancer. Furthermore, every 5 kg of weight reduction mediated by coagonists was also associated with a decreased risk of overall obesity‐related cancer.

Previous studies have raised concerns about whether the protective effect of weight loss against obesity‐related cancer depends more on the weight loss amount or the method used. Some studies indicated that weight loss through lifestyle modifications combining diet and exercise might reduce cancer risk, particularly for metabolically sensitive cancers like endometrial and colorectal cancer, through mechanisms extending beyond weight reduction alone [6, 17, 18]. These lifestyle interventions may enhance systemic metabolic health by improving insulin sensitivity, optimizing lipid metabolism, and suppressing chronic inflammation, all recognized drivers of carcinogenesis [19, 20, 21, 22]. In contrast, AOMs often target single pathways like appetite suppression or nutrient absorption blockade, potentially limiting their benefits to weight loss itself [23]. Bariatric surgery, despite its invasiveness, was significantly associated with risk reduction of obesity‐related cancer in a meta‐analysis (RR = 0.59, 95% CI: 0.39 to 0.90, p = 0.01) [24]. It achieved substantially greater weight loss (> 20% of initial weight) compared to AOMs or lifestyle interventions [25]. Overall, both the degree and approach to weight loss could influence cancer prevention.

Based on the prior discussion, four key hypotheses in the following paragraphs may explain the overall findings concerning the insignificant association between weight loss mediated by AOMs and the obesity‐related cancer risk.

First, the relatively short follow‐up periods in most AOM clinical trials (mostly 1–2 years) may be insufficient to capture obesity‐related cancer events, which typically require 5 to 10 years of molecular evolution. And since participants often enter trials with years of obesity‐related metabolic disorders, detected cancers might primarily reflect pretreatment molecular damage accumulation rather than drug effects, obscuring long‐term benefits.

Second, pharmacologically induced weight loss may partially mitigate certain features of obesity‐associated oncogenic microenvironments, such as chronic inflammation and hyperinsulinemia, but cannot fully reverse them, particularly in visceral adipose tissue (where inflammatory crown‐like structures persist) and hormone‐sensitive organs (e.g., breast and endometrium) that remain susceptible to estrogen‐driven carcinogenesis [26, 27].

Third, different AOMs may exert opposing influences. For example, phentermine's adrenergic effects may increase catecholamine levels, which could stimulate β‐adrenergic receptors on cancer cells to promote tumor metastasis in preclinical models [28, 29]. Topiramate's carbonic anhydrase inhibition might conversely exert antiangiogenic effects by acidifying the tumor microenvironment, thereby suppressing cancer development [30, 31]. Such counterbalancing effects could neutralize overall cancer risk modulation.

Fourth, AOM‐induced weight loss (typically 5%–15%) may fall below the threshold needed to disrupt oncogenic microenvironments, whereas the substantial weight loss from bariatric surgery (> 20%) is more likely to disrupt the underlying metabolic and inflammatory dysfunction [25, 32].

We also conducted the subgroup analyses to explore sources of the potential heterogeneity. The results showed no statistically significant differences among subgroups defined by age, BMI, sex, follow‐up duration, or diabetes status. These findings suggested that the lack of association between AOM‐mediated weight reduction and reduced obesity‐related cancer risk was consistent across patients with different baseline characteristics.

However, in the drug type subgroup, we found that only coagonists were statistically associated with a reduced risk of obesity‐related cancer, while other drug types, including GLP‐1RAs, triagonists, phentermine plus topiramate, and naltrexone plus bupropion, did not show a statistically significant association with risk reduction.

GLP‐1RAs, including liraglutide and semaglutide, reduce weight by activating GLP‐1 receptors, which slow gastric emptying and suppress appetite [33, 34]. While effective for weight management and cardiovascular risk reduction [35, 36], their impact on cancer risk remains inconsistent across studies [9, 10, 11, 13, 37, 38, 39]. Our study found no significant association with reduced obesity‐related cancer risk. In contrast, Wang et al. [10] reported significant associations between GLP‐1RAs and insulin and the risk reduction of 10 obesity‐related cancers in a retrospective cohort [10]. This divergence may stem from three factors, involving comparator effect, methodological differences, and patient characteristics. First, compared with placebo, insulin's potential procancer effects may amplify GLP‐1RAs' benefits in Wang et al.'s study [40]. Second, Wang et al.'s large real‐world cohort (1.7 million patients with 15‐year follow‐up) has a higher confounding risk versus our placebo‐controlled RCT meta‐analysis. Third, Wang et al.'s population exclusively with diabetes has a higher baseline cancer risk, whereas our broader cohorts with overweight or obesity may have obesity‐driven carcinogenesis as the dominant factor.

Coagonists, including tirzepatide (GLP‐1R/GIPR), cotadutide (GLP‐1R/GCGR), and cagrilintide (AMYR/CTR), target dual receptors to enhance weight loss and metabolic regulation. Our study suggested that their dual‐receptor targeting mechanism might confer additional benefits for cancer prevention, a novel finding requiring further validation to clarify underlying pathways.

Triagonists, including retatrutide, target three receptors (GLP‐1R, GIPR, and GCGR) to maximize weight loss [41]. Despite strong efficacy in weight management, our study found no significant cancer risk reduction, likely due to limited long‐term cancer risk data. More extensive studies are needed to fully assess their potential oncological benefits.

The combination of phentermine plus topiramate works by stimulating the sympathetic nervous system and regulating neurotransmitters to suppress appetite [42, 43]. The combination of naltrexone plus bupropion targets the brain's reward system to reduce food intake [44, 45]. They effectively reduce appetite and weight but show no significant cancer risk reduction in our analysis. Previous research has not extensively explored their effects on cancer risk, highlighting the need for more studies to evaluate their long‐term health effects.

Additionally, meta‐regression analysis was performed to evaluate factors influencing obesity‐related cancer outcomes in patients with overweight and obesity. Our analysis revealed no significant association between absolute weight reduction mediated by AOMs and the risk of overall obesity‐related cancer as well as other site‐specific cancers. Meanwhile, the weight reduction difference between AOMs and placebo groups was not associated with a reduced risk of overall cancer and other site‐specified cancers. In other words, the risk of most the obesity‐related cancer outcomes in AOM users was not associated with weight reduction mediated by AOMs (Tables S4, S5 and Figures S11, S12).

4.1. Limitations of Our Study

Our study also has several limitations. First, despite low statistical heterogeneity (all I² = 0%), clinically relevant differences across trials—such as patient characteristics, AOM types, and follow‐up durations—could still confound the results, even after using random‐effects models and subgroup analyses. Second, most trials had relatively short follow‐up periods, limiting the capacity to detect cancer outcomes. Third, by focusing only on pharmacological interventions, we could not compare their effects with established modalities like bariatric surgery (RR = 0.50, 95% CI: 0.37 to 0.67 for cancer risk reduction in recent meta‐analyses [46]) or intensive lifestyle changes. Finally, incomplete baseline data on cancer risk factors, including family history, genetics, and metabolic comorbidities, limited our ability to fully evaluate the impact of weight loss on cancer risk.

4.2. Recommendations for Future Research

Future studies should address these limitations by: (1) extending follow‐up duration and increasing sample sizes to better assess long‐term cancer risk; (2) including diverse weight‐loss interventions—such as lifestyle modifications and bariatric surgery—for comparative evaluation; (3) collecting comprehensive patient data on baseline risk factors and comorbidities to improve risk assessment; and (4) further investigating the mechanisms and long‐term effects of AOMs such as GLP‐1RAs and coagonists to support personalized treatment for patients with obesity and related conditions.

5. Conclusion

In this meta‐analysis, the weight reduction mediated by current AOM treatments was not associated with a reduced risk of prespecified obesity‐associated cancers in patients with overweight or obesity. However, a reduced risk of overall obesity‐related cancer was observed in patients treated with coagonists (tirzepatide, cotadutide, and cagrilintide). Further research is still needed to validate the findings.

Author Contributions

Xiaoling Cai, Chu Lin, and Linong Ji conceptualized this study. Chengwen Li and Chu Lin performed the study selection, data extraction, and statistical analyses, prepared the outlines, and wrote the manuscript. All authors contributed to the critical revision of manuscript drafts and approved the submitted version.

Conflicts of Interest

Linong Ji has received fees for lecture presentations and for consulting from AstraZeneca, Merck, Metabasis, MSD, Novartis, Eli Lilly, Roche, Sanofi‐Aventis, and Takeda. The other authors declared no conflicts of interest.

Supporting information

Table S1: Search strategy used for PubMed, Medline, Embase, the Cochrane Central Register of Controlled Trials, Web of Science and ClinicalTrials.gov database.

Table S2: Baseline characteristics of studies included in this meta‐analysis.

Table S3: RoB2 risk‐of‐bias assessment.

Table S4: Meta‐regression analysis for absolute weight reduction and the risk of overall cancer and site‐specified cancer in patients with overweight and obesity.

Table S5: Meta‐regression analysis for weight change difference between antiobesity medication (AOM)/placebo groups and the risk of overall cancer and site‐specified cancer in patients with overweight and obesity.

Figure S1: RoB2 risk‐of‐bias assessment.

Figure S2: The association between AOM treatments and the incidence of overall and site‐specified obesity‐related cancer.

Figure S3: The association between AOM treatments and the incidence of overall obesity‐related cancer stratified by drug types.

Figure S4: Standardized effect of every 5 kg body weight change on overall and site‐specified obesity‐related cancer risk.

Figure S5: Standardized effect of every 5 kg body weight change on overall obesity‐related cancer risk stratified by age.

Figure S6: Standardized effect of every 5 kg body weight change on overall obesity‐related cancer risk stratified by BMI.

Figure S7: Standardized effect of every 5 kg body weight change on overall obesity‐related cancer risk stratified by male percentage.

Figure S8: Standardized effect of every 5 kg body weight change on overall obesity‐related cancer risk stratified by follow‐up duration.

Figure S9: Standardized effect of every 5 kg body weight change on overall obesity‐related cancer risk stratified by diabetes status.

Figure S10: Standardized effect of every 5 kg body weight change on overall obesity‐related cancer risk stratified by drug type.

Figure S11: Meta‐regression analysis for absolute weight reduction and the risk of overall cancer in patients with overweight and obesity.

Figure S12: Meta‐regression analysis for weight change difference between AOM/placebo groups and the risk of overall cancer and site‐specified cancer in patients with overweight and obesity.

OBY-34-16-s001.pdf^{(3.4MB, pdf)}

Acknowledgments

We thank the doctors, nurses, and technicians for their practical work during the study at the Department of Endocrinology and Metabolism in Peking University People's Hospital.

Li C., Lin C., Cai X., Lv F., Yang W., and Ji L., “Weight Loss, Obesity Medication, and Risk of Obesity‐Associated Cancer: A Meta‐Analysis of Randomized Controlled Trials,” Obesity 34, no. S2 (2026): 16–24, 10.1002/oby.70054.

Funding: This work was supported by the Noncommunicable Chronic Diseases‐National Science and Technology Major Project (2023ZD0508200, 2023ZD0508205), the 2024 National Clinical Key Specialty Construction Program of China (Department of Endocrinology, Peking University People's Hospital) with support from the central government budget and Clinical Medicine Plus X‐Young Scholars Project of Peking University (PKU2025PKULCXQ025), and the Fundamental Research Funds for the Central Universities. The funding agencies had no roles in the study design, data collection or analysis, decision to publish, or preparation of the manuscript.

Contributor Information

Xiaoling Cai, Email: dr_junel@sina.com.

Linong Ji, Email: jiln@bjmu.edu.cn.

Data Availability Statement

The data that supports the findings of this study are available in the online Supporting Information of this article.

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