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Currently submitted to: JMIR mHealth and uHealth

Date Submitted: Jan 16, 2026

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Application of Intelligent Digital Monitoring for Colorectal Cancer Nutrition : A Systematic Review and Meta-analysis

  • Xiaoyi Cao; 
  • Yuyan Zhao; 
  • Li Niu; 
  • Zhuojing Yang; 
  • Juzi Wang

ABSTRACT

Background:

Intelligent digital monitoring–supported nutrition management has emerged as a scalable approach to deliver longitudinal nutrition care for adults with colorectal cancer (CRC) by repeatedly capturing nutrition-relevant indicators and enabling timely,data-driven feedback and adjustments.However,the effectiveness of these monitoring-driven programs across key nutritional and patient-centered outcomes has not been comprehensively synthesized. Therefore,this systematic review and meta-analysis aims to evaluate the effects of intelligent digital monitoring–supported nutrition management on dietary intake, anthropometric changes, nutri-tional status, quality of life,and nutrition-related biochemical markers in adults with CRC.

Objective:

This systematic review and meta-analysis aims to evaluate the effects of intelligent digital monitoring–supported nutrition management on dietary intake, anthropomet-ric changes, nutritional status, quality of life,and nutrition-related biochemical markers in adults with CRC.

Methods:

In this systematic review and meta-analysis,we searched PubMed, Web of Sci-ence,Embase,Scopus,ProQuest, the Cochrane Library,CNKI,Wanfang, VIP Data-base,and SinoMed from inception to November 2025, without language re-strictions.We included randomized controlled trials (RCTs), non-randomized con-trolled studies (NRCTs), and prospective study.Two reviewers independently screened records and extracted data, and assessed methodological quality using RoB 2 for randomized trials and ROBINS-I for non-randomized studies. When appropri-ate, pooled effects were synthesized using random-effects models and reported as mean differences (MDs) or standardized mean differences (SMDs) with 95% CIs.

Results:

A total of 15 studies were included (7 RCTs, 6 NRCTs, and 2 prospective studies), comprising 1,235 participants. The studies were conducted in China, the United States, the Netherlands, and Thailand, with an average age of approximately 46–85 years. Meta-analysis showed that intelligent digital monitoring could significantly increase energy intake (MD = 257.32, 95% CI 177.71–336.93, I² = 41%), reduce body weight(MD = 3.00,95% CI 2.03–3.97,I² = 0%),and improved nutritional status, as reflected by a lower Patient-Generated Subjective Global Assessmen(PG-SGA) scores (MD 1.60, 95% CI 1.35–1.84; I²=16%).The combined effect on quality of life (QoL) suggested potential benefits, but heterogeneity was extremely high (I²=96%).Among nutrition-related biochemical indicators,prealbumin(PAB) results were relatively consistent (I²=0%), whereas total protein (TP), albumin (ALB) and hemoglobin (Hb) exhibited significant heterogeneity (I²≥89%).

Conclusions:

Current evidence suggests that intelligent digital monitoring–supported nutrition management may improve energy intake in adults with CRC and confer potential benefits for body weight and nutritional status. However, findings for QoL and some biochemical markers remain inconsistent. Future adequately powered, well-standardized trials are needed to establish reproducible closed-loop “monitor–feedback and threshold-trigger–adjust” models and to test whether effects vary by tumor stage, treatment phase, the mode and intensity of professional follow-up, and the level of family and caregiver involvement. Clinical Trial: We registered this review in PROSPERO (CRD420251218785).


 Citation

Please cite as:

Cao X, Zhao Y, Niu L, Yang Z, Wang J

Application of Intelligent Digital Monitoring for Colorectal Cancer Nutrition : A Systematic Review and Meta-analysis

JMIR Preprints. 16/01/2026:91224

DOI: 10.2196/preprints.91224

URL: https://preprints.jmir.org/preprint/91224

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