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Clinical Decision Support

Generate publication-ready clinical decision support documents with biomarker analyses and GRADE ...

4.5(49 reviews)
1,000+ downloads
Updated Nov 2026
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What You Can Do

You can generate publication-ready clinical decision support documents that synthesize complex clinical evidence into actionable recommendations. This skill produces biomarker-stratified patient cohort analyses with statistical outcome comparisons, and treatment recommendation reports featuring GRADE evidence grading, decision algorithms, and regulatory-compliant formatting. Documents are optimized for pharmaceutical research, clinical guidelines, and regulatory submissions.

Features

Biomarker-stratified patient cohort analysis

segment patient populations by molecular subtypes, gene expression, or immunohistochemistry markers with comparative outcomes

GRADE evidence grading

systematically classify evidence quality and recommendation strength across treatment options

Statistical outcome reporting

generate hazard ratios, survival curves, waterfall plots, and comparative efficacy data with proper statistical notation

Treatment recommendation algorithms

develop decision trees and clinical pathways based on patient characteristics and evidence hierarchy

Publication-ready LaTeX/PDF output

automatically format documents meeting pharmaceutical journal and regulatory submission standards

Evidence synthesis integration

consolidate clinical trial data, real-world evidence, and guideline recommendations into structured reports

Regulatory compliance formatting

ensure documents meet ICH, FDA, and EMA standards for clinical documentation

Example Output

Example 1: Biomarker-Stratified Cohort Analysis

Patient SubgroupNMedian OS (months)Hazard RatioGRADE Quality
PD-L1 High (≥50%)14524.30.61 (0.48-0.78)Moderate
PD-L1 Low (<50%)8918.10.89 (0.65-1.21)Low

Example 2: Treatment Recommendation Report

Recommendation 1 (GRADE: Strong, Moderate quality evidence): First-line immune checkpoint inhibitor monotherapy for PD-L1 high patients based on randomized controlled trial data (RCT n=234, HR=0.61).

Recommendation 2 (GRADE: Conditional, Low quality evidence): Consider combination chemotherapy for PD-L1 low patients given limited immunotherapy benefit and supporting observational data.

What's Included

  • SKILL.md instruction file with clinical decision support protocols and document templates:
  • Biomarker stratification framework: molecular subtype classification and cohort definition templates
  • GRADE evidence grading checklist: systematic approach to rating evidence quality and recommendation strength
  • Statistical outcomes template: standardized format for hazard ratios, survival analysis, and comparative efficacy reporting
  • Treatment recommendation algorithm template: decision tree structure for evidence-based clinical pathways
  • LaTeX/PDF formatting styles: publication-ready templates compliant with pharmaceutical journal standards

Who It's For

  • Clinical researchers and drug development teams synthesizing evidence for pharmaceutical compounds
  • Medical directors and evidence committees developing institutional clinical guidelines
  • Regulatory affairs professionals preparing clinical evidence dossiers for submissions
  • Biostatisticians and epidemiologists creating comparative effectiveness analyses
  • Medical writers developing clinical decision support materials for healthcare organizations

Best For

  • Generating biomarker-driven patient stratification analyses for precision medicine studies
  • Creating GRADE-based treatment recommendation reports for clinical guidelines
  • Synthesizing multi-trial evidence into structured comparative effectiveness documents
  • Developing regulatory-compliant clinical decision support for drug approval submissions
  • Building evidence-based clinical algorithms and decision pathways for treatment selection

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