Pith Number

pith:N7HB2FZK

pith:2026:N7HB2FZK5EI4MN233FAFTME7FL

not attested not anchored not stored refs pending

Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments

Donglin Zeng, Hyun-Joon Yang, Leanne M. Williams, Yuan Bian, Yuanjia Wang

Multiple randomized trials sharing one treatment arm can be combined to estimate more accurate individualized treatment rules than analyzing each trial alone.

arxiv:2604.10712 v2 · 2026-04-12 · stat.ME · stat.AP

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\usepackage{pith}
\pithnumber{N7HB2FZK5EI4MN233FAFTME7FL}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We propose an integrative learning framework that synthesizes evidence across multiple RCTs that share a common comparator but differ in their alternative treatment arms. Our method integrates information through a regularized weighted misclassification risk function and adaptively determines the contribution of each study to the ITRs of the others.

C2weakest assumption

That the common comparator treatment allows unbiased transfer of information about treatment effect heterogeneity across studies despite possible differences in patient populations, study designs, or unmeasured confounders.

C3one line summary

A new integrative framework estimates individualized treatment rules by pooling data from multiple RCTs sharing a common comparator treatment, using regularized weighted misclassification risk and adaptive study weighting, with improvements shown in simulations and two depression studies.

Receipt and verification

First computed	2026-06-03T02:05:47.542770Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

6fce1d172ae911c6375bd94059b09f2adf028f7a9a71d89def8b7ce4376ec3c6

Aliases

arxiv: 2604.10712 · arxiv_version: 2604.10712v2 · doi: 10.48550/arxiv.2604.10712 · pith_short_12: N7HB2FZK5EI4 · pith_short_16: N7HB2FZK5EI4MN23 · pith_short_8: N7HB2FZK

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/N7HB2FZK5EI4MN233FAFTME7FL \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 6fce1d172ae911c6375bd94059b09f2adf028f7a9a71d89def8b7ce4376ec3c6

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "aaed4c43efb4866dbb9a875294156bd8ae85d4c3c8fdee45a08c9808f9e32dec",
    "cross_cats_sorted": [
      "stat.AP"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ME",
    "submitted_at": "2026-04-12T16:12:14Z",
    "title_canon_sha256": "4847c19ec2416062426fb900651c073aa7f72b150b4ab86808b857c4436d89e8"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.10712",
    "kind": "arxiv",
    "version": 2
  }
}