Multimodal Digital Health Interventions versus Standard Perioperative Management in Lung Cancer Surgery: A Systematic Review, Meta-Analysis, and Evidence Gap Map

Technical Summary: Multimodal Digital Health Interventions versus Standard Perioperative Management in Lung Cancer Surgery

1. Problem Statement

Lung cancer surgery, particularly for early-stage non-small cell lung cancer (NSCLC), presents significant perioperative challenges, including high rates of postoperative pulmonary complications (PPCs), protracted pulmonary function recovery, and substantial symptom burdens (pain, anxiety, depression) that degrade health-related quality of life (HRQoL). While traditional multidisciplinary team (MM) management is the standard of care, it faces constraints regarding human resource intensity, geographic inequity, and fragmented post-discharge continuity.

Multimodal Digital Health Interventions (DHIs)—defined here as integrated systems combining two or more distinct digital modalities (e.g., wearables, mobile apps, remote monitoring, AI decision support, and ePRO systems)—have emerged as potential alternatives. However, prior systematic reviews have failed to:

• Quantitatively compare multimodal DHIs specifically against formal multidisciplinary management (MM).
• Distinguish synergistic multi-component platforms from single-function digital tools.
• Map evidence across clinical endpoints, patient-reported outcomes (PROs), and implementation metrics (e.g., management time, cost).
• Integrate Chinese and international evidence into a unified landscape.

Consequently, the comparative effectiveness and implementation value of multimodal DHIs in lung cancer surgery remain systematically unmapped.

2. Methodology

This study is a systematic review, meta-analysis, and evidence gap map registered with PROSPERO (CRD420261417858) and conducted according to PRISMA 2020 guidelines.

• Search Strategy: A comprehensive search was performed across ten databases (including PubMed, EMBASE, CNKI, Wanfang) from inception to June 2026, supplemented by trial registries, grey literature, and conference proceedings.
• Eligibility Criteria:
  • Population: Adults (≥18) undergoing lung cancer surgery (lobectomy, sublobar resection, pneumonectomy).
  • Intervention: Multimodal DHIs incorporating ≥2 distinct digital modality categories.
  • Comparator: Tiered framework including formal MM (≥3 disciplines), conventional perioperative management (usual care/ERAS), and single-modality digital interventions.
  • Study Design: Parallel-group RCTs and quasi-experimental controlled studies (minimum 10 participants per arm).
• Data Synthesis:
  • Quantitative: Random-effects meta-analysis (REML estimator) was used for compatible RCTs. Outcomes included pulmonary function (FEV1%, FVC, PaO2), PPCs, length of stay (LOS), pain, anxiety/depression, HRQoL, and management time.
  • Qualitative: Non-randomized studies and incompatible data were synthesized narratively using the Synthesis Without Meta-analysis (SWiM) guidelines.
  • Bias and Certainty: Risk of bias was assessed via RoB 2.0 (RCTs) and ROBINS-I (non-randomized). Evidence certainty was rated using GRADE.
• Gap Mapping: An evidence gap map was constructed to visualize the distribution of evidence across outcome domains and comparator types.

3. Key Contributions

• Unified Evidence Base: The review integrates an initial search and a supplementary "gap-fill" search into a single coherent dataset of 11 controlled studies (2,088 participants), avoiding the presentation of missed studies as separate post-hoc analyses.
• Strict Multimodal Definition: The study operationalizes "multimodal" as requiring ≥2 distinct digital categories, distinguishing synergistic closed-loop care pathways from single-function digitization.
• Tiered Comparator Analysis: It explicitly stratifies comparisons against formal multidisciplinary management (the clinical gold standard) versus usual care, addressing a critical gap in previous literature.
• Evidence Gap Mapping: Beyond traditional meta-analysis, the study provides a structural visualization of research voids, specifically highlighting the scarcity of direct DHI-vs-MM comparisons and economic evaluations.
• Implementation Focus: It evaluates healthcare personnel management time, finding a specific study demonstrating a 91.1% reduction in management time for digital therapeutics compared to MM.

4. Results

Eleven studies (8 RCTs, 3 non-randomized) were included. The certainty of evidence was rated as very low to insufficient across all outcomes due to open-label designs, heterogeneity, imprecision, and risk of bias.

• Pulmonary Function: Meta-analysis of 3 RCTs (n=345) favored multimodal DHIs (SMD 0.705, 95% CI 0.137 to 1.272), though heterogeneity was substantial (I²=83.9%). A sensitivity analysis including a fourth study via median/IQR conversion supported this directional trend (SMD 0.607).
• Health-Related Quality of Life (HRQoL): Four RCTs (n=438) showed a significant improvement in HRQoL with DHIs (SMD 0.647, 95% CI 0.276 to 1.018), with moderate heterogeneity (I²=67.9%).
• Length of Stay (LOS): Two RCTs (n=242) indicated a directional trend toward shorter LOS with DHIs, but the result was statistically inconclusive and highly heterogeneous (MD -0.804 days, 95% CI -2.542 to 0.934; I²=89.6%). One study comparing DHIs to formal MM showed almost identical LOS.
• Psychological Outcomes: Single-study analyses (Sui 2020) indicated significant reductions in anxiety (RR 0.463) and depression (RR 0.556) rates. Other studies reported favorable signals but lacked compatible data for pooling.
• Postoperative Pulmonary Complications (PPCs) & Pain: These outcomes could not be meta-analyzed due to incompatible endpoint definitions (e.g., exclusion of severe complications in one trial, reporting of readmissions rather than Clavien-Dindo grades in another) and reporting formats (median/IQR vs. mean/SD).
• Management Time: One RCT (Xu et al.) reported a massive reduction in management time for DHIs (1.48 min/patient) compared to MM (16.67 min/patient), representing a 91.1% reduction.
• Non-Randomized Evidence: Three non-randomized studies supported the direction of benefit for activity levels, dyspnea, and pulmonary function but were synthesized narratively due to serious confounding risks.

5. Significance and Claims

The paper claims that multimodal DHIs show promising but very low-certainty evidence as adjuncts to perioperative supportive care for lung cancer surgery.

• Clinical Translation: The authors assert that DHIs should be viewed as adjunctive tools rather than replacements for multidisciplinary teams. They may extend monitoring and rehabilitation feedback in tertiary centers or improve post-discharge continuity in resource-limited settings, provided escalation pathways are established.
• Research Gaps: The evidence gap map identifies critical voids:
  1. Direct Comparisons: Only one RCT directly compared multimodal DHIs to formal MM; replication is needed to establish non-inferiority.
  2. Economic Data: No studies reported cost-effectiveness or cost-utility outcomes.
  3. Long-term Outcomes: Survival and durable functional recovery are rarely reported.
  4. Underserved Populations: Older adults, those with cognitive impairment, and patients with low digital literacy are systematically underrepresented.
• Future Directions: The paper calls for future trials to standardize outcome reporting, directly compare DHIs with multidisciplinary management, evaluate implementation and equity, and conduct economic evaluations using hybrid effectiveness-implementation frameworks.

The authors maintain a modest stance, emphasizing that current evidence supports "cautious adjunctive integration" while underscoring the necessity for rigorous, standardized, and implementation-focused trials to validate these interventions.