Combined with the digital whole process management data pool, a multi-modal data fusion framework is developed, and an AI model is established to realize risk stratification and personalized treatment Recommendation and dynamic prognosis prediction; validation of whole-process management based on multimodal digital fusion AI-aided decision support system through prospective non-randomized controlled interventional study The effect on survival, complication control and utilization of medical resources in patients with comorbid malignant tumors.
Patients with a definite diagnosis of malignancy by histopathology and/or cytology;
Age ≥18 years;
There is no gender limit
Plan to receive antineoplastic therapy within 2 weeks or are receiving standard antineoplastic care (surgery, radiation, chemotherapy, or targeted therapy) ;
Having severe mental or cognitive impairments that prevent them from understanding the content of the study or implementing the programme;
With severe heart disease, acute respiratory failure, liver kidney failure and other critical illness;
Women during pregnancy or lactation；
Have participated in other interventional studies in the past 1 month or are currently participating;
Parallel
AI-assisted comprehensive management system
Other interventionPrecision Risk Stratification and personalized treatment recommendation through AI models may improve the suitability of treatment regimens and thus reduce the incidence of antineoplastic therapy-related adverse effects (e.g. , reduction of chemotherapy toxicity through nutritional intervention) , and improve the efficacy of chemotherapy, and prolonged progression-free survival (PFS) and overall survival (OS)
Progression-free survival (PFS)
Progression-free survival (PFS) : the time from randomization (or study enrollment) to the observation of disease progression or the occurrence of death from any cause. This period was assessed every 6-8 weeks using RECIST 1.1 criteria.
Overall survival (OS）
Overall survival (OS） : the time from study enrollment to death from any cause from any cause, every 3 months during treatment, and every 3 months after the end of treatment. The patients were followed up at 6 months and the cause of death was recorded.
Comorbidity control rate.
Comorbidity control rate: the proportion of comorbidities achieving guideline-recommended control targets during the study period; stratified criteria should be established based on specific comorbidity types.
Quality of life(QLQ-C30).
Quality of life: changes in scores at baseline, on-treatment, and follow-up were assessed using the European Organisation for Research and Treatment of Cancer QLQ-C30 scale, between-group differences
Medical resource consumption index.
Medical resource consumption index: Comparing DRG-adjusted medical resource consumption indices between two groups.
Adherence to AI system interventions.
Adherence to AI Interventions: 1. In-Hospital Rate - Percentage of inpatients completing AI-recommended actions (e.g., nutritional screening, real-time monitoring). 2. Out-of-Hospital Completion Rate: Percentage of discharged/outpatients adhering to AI-guided care (e.g., telehealth, wearable data tracking). Enables precise evaluation of AI-driven care across clinical settings.
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