JMIR Publications

ABSTRACT

Background:

Cancer-related fatigue (CRF) affects 60–90% of cancer patients yet remains underreported. Heart rate variability (HRV) via wearable devices offers passive symptom monitoring. Prior work showed strong LF/HF–fatigue correlation (ρ = 0.86) in lung cancer, but generalizability to multi-cancer populations is unknown.

Objective:

This study aimed to evaluate whether three complementary wearable HRV-derived metrics—night LF/HF mean (autonomic level), LF/HF SD (autonomic instability), and the sleep-phase disorder ratio (episodic dysregulation)—can screen for multiple cancer symptoms in hospitalized patients with mixed cancer types.

Methods:

Forty-six hospitalized cancer patients (lung 28%, colorectal 22%, breast 13%, other 37%) wore PPG-based smart wristbands continuously while completing the Brief Fatigue Inventory (BFI), Edmonton Symptom Assessment System (ESAS), and Pittsburgh Sleep Quality Index (PSQI). Three HRV-derived metrics were examined: night LF/HF mean (autonomic level), LF/HF standard deviation (SD; autonomic instability), and the sleep-phase LF/HF disorder ratio (DR; episodic dysregulation).

Results:

The disorder ratio yielded nearly double the significant correlations of conventional HRV (28.6% vs. 15.1%). For breathlessness ≥ 4, night LF/HF achieved AUC = 0.868 (100% sensitivity). In combined models controlling for mean LF/HF, LF/HF SD was the only metric to independently predict BFI Total (P=.048) and ESAS Fatigue (P=.049). Night LF/HF and DR predicted somatic symptoms; LF/HF SD uniquely predicted fatigue.

Conclusions:

The complementary three-metric framework—level, instability, and episodic dysregulation—captures distinct symptom pathways and extends the LF/HF–fatigue relationship to heterogeneous cancer populations. Clinical Trial: N/A