Four complementary causal analysis methods explore whether Oura biometrics
shifted after ruxolitinib
(10 mg BID, started 2026-03-16) on Oura Ring biometrics.
Data period: 2026-01-08 to 2026-05-09
(122 days).
Lowest raw p
Not significantp=1.000
N/A | q=1.0000
4
CI + PCMCI+ + TE + Mediation
0. Individual Metric Treatment Response
Method: Non-parametric Mann-Whitney U test compares pre- vs post-ruxolitinib distributions for each core biometric. Effect sizes reported as Cohen's d with bootstrap 95% CI (2000 iterations). These direct statistical tests provide intuitive per-metric significance before the multivariate causal methods below.
Sleep Efficiency
Significantp<0.001
d=+0.66 (medium)
| Metric |
Pre-Rux Mean |
Post-Rux Mean |
Change |
Cohen's d |
Mann-Whitney |
95% CI (diff) |
| HRV (RMSSD) | 10.00 ms | 22.87 ms | +12.88 ms | +1.54 (large) | Sig p<0.001 | [+9.74, +16.31] |
| Lowest HR | 76.72 bpm | 66.52 bpm | -10.20 bpm | -1.57 (large) | Sig p<0.001 | [-12.62, -7.76] |
| Average HR | 85.17 bpm | 74.92 bpm | -10.25 bpm | -1.42 (large) | Sig p<0.001 | [-12.97, -7.69] |
| Sleep Efficiency | 78.62 % | 81.40 % | +2.78 % | +0.66 (medium) | Sig p<0.001 | [+1.02, +4.34] |
Note: These per-metric tests complement the Bayesian CausalImpact analysis below. For full changepoint detection and multi-patient comparison, see the
Comparative Treatment Response report.
1. CausalImpact - Bayesian Structural Time Series Analysis
Method: Bayesian Structural Time Series (BSTS) models pre-intervention dynamics and generates a counterfactual prediction for the post-period. The difference between actual and counterfactual estimates the causal effect, with full posterior uncertainty. MCMC: 5,000 iterations, weekly seasonal component (nseasons=7). Benjamini-Hochberg FDR correction for multiple testing.
FAILED CausalImpact package not installed. Install with: pip install pycausalimpact
1a. Statistical Power & Interpretation
Purpose: All 11 metrics sorted by statistical significance, with Benjamini-Hochberg corrected q-values for multiple testing.
No CausalImpact results available for statistical power analysis.
1b. Placebo tests (intervention date falsification)
Method: CausalImpact is run with 3 random placebo dates in the pre-period on the 3 most significant metrics. Placebo dates should NOT show significant effects.
CausalImpact failed, skipping placebo
2. Granger Causality Network (PCMCI+)
Method: PCMCI+ (tigramite) tests for time-lagged causal relationships between biometric variables using partial correlation. Tau_max = 7 days.
Full period (0 days): No significant causal links found.
Pre-ruxolitinib (0 days): No significant causal links found.
3. Transfer Entropy
Method: Transfer entropy quantifies directional information flow between biometric streams. Comparison of TE matrices for pre- and full period reveals changes in information coupling after ruxolitinib start.
Full period (121 days)
| Source | Target | TE (bits) | Net TE |
|---|
| TotalSleep | LowestHR | 0.7815 | +0.2621 |
| DeepDur | LowestHR | 0.7815 | +0.2030 |
| SpO2 | LowestHR | 0.7815 | +0.1262 |
| REMpct | LowestHR | 0.7581 | +0.1604 |
| SpO2 | RespRate | 0.7544 | +0.1160 |
| REMdur | RespRate | 0.7374 | +0.2222 |
| TotalSleep | RespRate | 0.7374 | +0.2181 |
| DeepDur | RespRate | 0.7374 | +0.1759 |
Pre-ruxolitinib (67 days)
| Source | Target | TE (bits) | Net TE |
|---|
| REMdur | RespRate | 0.5564 | +0.1891 |
| TotalSleep | RespRate | 0.5564 | +0.3064 |
| DeepDur | RespRate | 0.5564 | +0.2439 |
| RMSSDmax | RespRate | 0.5564 | +0.3689 |
| LowestHR | RespRate | 0.5564 | +0.2127 |
| AvgHR | RespRate | 0.5564 | +0.1071 |
| SpO2 | RespRate | 0.5564 | +0.1132 |
| REMpct | RespRate | 0.5252 | +0.0835 |
Change in information flow
Largest increase: REMpct -> LowestHR (+0.4456 bits)
Largest decrease: REMdur -> REMdur (+0.0000 bits)
5. Clinical Interpretation
Executive summary
N/A
Strongest signal: p=1.000
0/0
Metrics trending in expected direction
55
Post-intervention days (Day 14 target)
- N/A: strongest hypothesis-generating raw p-value signal
(p=1.0000, q=1.0000). It does not survive
FDR correction, so confirmation still depends on more post-treatment follow-up.
- CausalImpact: 0 of 0 biometric streams show
significant causal change (p < 0.05). After Benjamini-Hochberg FDR correction:
0 of 0 remain significant (q < 0.05).
- Placebo validation: N/A - ?/?
placebo tests reached significance. This keeps the result vulnerable to false positives
rather than establishing a confirmed intervention effect.
- PCMCI+: 0 significant time-lagged causal links
identified in the biometric network
- Mediation analysis: 3 of 4 mediating pathways
show significant indirect effect
Limitations
- Short post-period (55 days): All results are preliminary.
Minimum 14-21 days of post-intervention data recommended for robust causal inference.
- Confounders: Linear methods cannot capture non-linear interactions.
Seasonal variation, activity level, and other medications are not controlled for.
- Wearable data: Oura Ring is not a medical device.
Measurements have inherent noise that can affect causal estimates.
- Single patient: N=1 study without control group. Causality cannot be
definitively established, but Bayesian posterior probability of effect provides a strength measure.
- HEV diagnosis: HEV was diagnosed 2026-03-18 (2 days after
ruxolitinib start). Hepatitis may confound biometric changes.
Recommendations
- Repeat analysis after 2-3 weeks of ruxolitinib treatment for robust causal inference
- Add HEV-related biomarkers (ALT, bilirubin) as time-varying covariates
- Consider synthetic control method when longer time series are available
- Combine with clinical endpoints (GVHD scoring, ferritin) for multimodal analysis