OpenClaw-Medical-Skills mpn-progression-monitor-agent

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T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/mpn-progression-monitor-agent" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-mpn-progression-monitor-agent && rm -rf "$T"
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T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/mpn-progression-monitor-agent" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-mpn-progression-monitor-agent && rm -rf "$T"
manifest: skills/mpn-progression-monitor-agent/SKILL.md
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name: 'mpn-progression-monitor-agent' description: 'AI-powered myeloproliferative neoplasm monitoring for disease progression prediction, treatment response tracking, and transformation risk assessment in PV, ET, and myelofibrosis.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

MPN Progression Monitor Agent

The MPN Progression Monitor Agent provides comprehensive monitoring of myeloproliferative neoplasms (PV, ET, MF) for disease progression, treatment response, and transformation risk. It integrates molecular profiling, clinical parameters, and AI-based risk models to guide management of chronic phase disease and predict blast transformation.

When to Use This Skill

  • When monitoring JAK2/CALR/MPL mutation burden over time.
  • For predicting fibrosis progression in PV/ET.
  • To assess risk of blast transformation.
  • When tracking treatment response to JAK inhibitors.
  • For calculating dynamic risk scores (DIPSS, MIPSS70).

Core Capabilities

  1. Mutation Monitoring: Track driver and high-risk mutation VAF.

  2. Progression Prediction: Model fibrosis and transformation risk.

  3. Risk Scoring: Calculate DIPSS, MIPSS70+, MTSS dynamically.

  4. Treatment Response: Assess molecular and clinical response.

  5. Clone Evolution: Track clonal dynamics and new mutations.

  6. Transplant Timing: Optimize allo-HSCT timing decisions.

MPN Classification

MPN TypeDriver MutationsProgression Risk
PVJAK2 V617F (95%), JAK2 exon 12Fibrosis 10-15%, AML 2-5%
ETJAK2 (55%), CALR (25%), MPL (5%)Fibrosis 5-10%, AML 1-2%
Pre-PMFSame as PMFVariable
PMFJAK2 (60%), CALR (25%), MPL (5%)AML 10-20%

High-Risk Mutations

MutationImpactMF Association
ASXL1AdverseStrong
SRSF2AdverseStrong (PMF)
EZH2AdverseModerate
IDH1/2AdverseTransformation
RUNX1Very AdverseTransformation
TP53Very AdverseTransformation
U2AF1AdverseModerate

Risk Scores

ScoreComponentsApplication
IPSSAge, Hb, WBC, blasts, symptomsPMF at diagnosis
DIPSSSame, dynamicPMF follow-up
DIPSS++ karyotype, transfusion, plateletsPMF refined
MIPSS70Molecular markersTransplant-age PMF
MIPSS70+ v2.0+ U2AF1, karyotypeMost comprehensive
MTSSTransplant-specificAllo-HSCT outcomes

Workflow

  1. Input: Serial molecular testing, CBC, clinical parameters.

  2. Baseline Assessment: Calculate initial risk score.

  3. Mutation Tracking: Monitor VAF trends over time.

  4. Risk Recalculation: Update scores at each timepoint.

  5. Progression Detection: Identify molecular/clinical progression.

  6. Treatment Assessment: Evaluate response to therapy.

  7. Output: Dynamic risk assessment, progression alerts, recommendations.

Example Usage

User: "Monitor this myelofibrosis patient's disease trajectory and update risk scores with new molecular data."

Agent Action:

python3 Skills/Hematology/MPN_Progression_Monitor_Agent/mpn_monitor.py \
    --patient_id MF_001 \
    --molecular_data serial_mutations.csv \
    --cbc_data serial_cbc.csv \
    --clinical_data symptoms.json \
    --mpn_type pmf \
    --baseline_date 2024-01-15 \
    --calculate_scores dipss,mipss70 \
    --output mpn_monitoring/

Input Requirements

Data TypeParametersFrequency
MolecularJAK2/CALR/MPL VAF, NGS panelq3-6 months
CBCHb, WBC, platelets, blastsMonthly
ClinicalSymptoms, spleen sizeq3 months
Bone MarrowFibrosis grade, cytogeneticsq6-12 months

Output Components

OutputDescriptionFormat
Risk ScoresDIPSS, MIPSS70 over time.csv
VAF TrendsMutation burden plots.png
Progression AlertWarning if criteria met.json
Response AssessmentIWG-MRT criteria.json
Transplant TimingRecommendation if indicated.json
Clone EvolutionNew mutations, clonal shifts.csv

Progression Criteria

Progression TypeCriteriaAction
ClinicalNew symptoms, splenomegalyIntensify therapy
HematologicCytopenias, increased blastsBMB, cytogenetics
MolecularNew high-risk mutationsRisk restaging
FibroticIncreased fibrosis gradeConsider transplant
Blast Phase≥20% blastsUrgent intervention

Response Criteria (IWG-MRT)

ResponseDefinitionImplications
Complete RemissionNo disease manifestationsExcellent outcome
Partial Remission>50% improvementGood response
Clinical ImprovementSymptom/spleen improvementBenefit
Stable DiseaseNo changeObserve
Progressive DiseaseProgression criteriaChange therapy

AI/ML Components

Progression Prediction:

  • Survival analysis with molecular features
  • Random survival forests
  • Deep learning time-to-event

Clone Tracking:

  • VAF trajectory modeling
  • New clone detection
  • Evolutionary tree inference

Transplant Decision:

  • Survival benefit modeling
  • NRM prediction
  • Optimal timing algorithms

Treatment Response Monitoring

TherapyResponse MarkersTimeline
RuxolitinibSpleen, symptoms, JAK2 VAF12-24 weeks
FedratinibSimilar to ruxolitinib24 weeks
Momelotinib+ anemia improvement24 weeks
InterferonMolecular response, JAK2 VAF12+ months

Prerequisites

  • Python 3.10+
  • lifelines, scikit-survival
  • Variant annotation tools
  • Risk score calculators
  • Visualization libraries

Related Skills

  • CHIP_Clonal_Hematopoiesis_Agent - Pre-MPN states
  • MDS_Classification_Agent - Overlap syndromes
  • Bone_Marrow_AI_Agent - Morphology analysis
  • Coagulation_Thrombosis_Agent - Thrombosis risk

Thrombosis Risk in MPN

FactorRisk IncreaseManagement
Age >602-3xCytoreduction
Prior thrombosis3-5xAnticoagulation
JAK2 V617F2xHigher for homozygous
High WBC1.5-2xControl counts
CV risk factorsAdditiveAggressive management

Special Considerations

  1. Triple-Negative MPN: Different prognosis, consider other diagnoses
  2. Cytogenetic Evolution: High-risk signal, BMB follow-up
  3. New Mutations: May indicate disease evolution
  4. Treatment Resistance: Consider second-line or transplant
  5. Quality of Life: Balance treatment intensity

Transplant Indications

IndicationCriteriaTiming
High-Risk PMFMIPSS70+ high/very highConsider early
Blast Phase≥20% blastsUrgent if fit
Refractory DiseaseFailed JAKiEvaluate
Transfusion DependenceRBC/platelet dependentFactor in decision

Author

AI Group - Biomedical AI Platform

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