Mpn Progression Monitor Agent

AI-powered myeloproliferative neoplasm monitoring for disease progression prediction, treatment response tracking, and transformation risk assessment in PV, ET, and myelofibrosis.

FridrichMethod Updated Sep 17, 2026

Install

Press C to copy

$ npx skillmds@latest add fridrichmethod/mpn-progression-monitor-agent

Installs into ~/.claude/skills (or .claude/skills inside a project). Restart Claude Code to pick it up.

Download SKILL.md

＋ Add to collection

README badge

[![SkillMD](https://skillmd.com/badge/fridrichmethod/mpn-progression-monitor-agent.svg)](https://skillmd.com/skills/fridrichmethod/mpn-progression-monitor-agent)

Trust & safety

Audits pending

Not yet audited · commit 40c7098

Works with: Claude Code Claude.ai OpenAI Codex +

File contents

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

Mutation Monitoring: Track driver and high-risk mutation VAF.
Progression Prediction: Model fibrosis and transformation risk.
Risk Scoring: Calculate DIPSS, MIPSS70+, MTSS dynamically.
Treatment Response: Assess molecular and clinical response.
Clone Evolution: Track clonal dynamics and new mutations.
Transplant Timing: Optimize allo-HSCT timing decisions.

MPN Classification

MPN Type	Driver Mutations	Progression Risk
PV	JAK2 V617F (95%), JAK2 exon 12	Fibrosis 10-15%, AML 2-5%
ET	JAK2 (55%), CALR (25%), MPL (5%)	Fibrosis 5-10%, AML 1-2%
Pre-PMF	Same as PMF	Variable
PMF	JAK2 (60%), CALR (25%), MPL (5%)	AML 10-20%

High-Risk Mutations

Mutation	Impact	MF Association
ASXL1	Adverse	Strong
SRSF2	Adverse	Strong (PMF)
EZH2	Adverse	Moderate
IDH1/2	Adverse	Transformation
RUNX1	Very Adverse	Transformation
TP53	Very Adverse	Transformation
U2AF1	Adverse	Moderate

Risk Scores

Score	Components	Application
IPSS	Age, Hb, WBC, blasts, symptoms	PMF at diagnosis
DIPSS	Same, dynamic	PMF follow-up
DIPSS+	+ karyotype, transfusion, platelets	PMF refined
MIPSS70	Molecular markers	Transplant-age PMF
MIPSS70+ v2.0	+ U2AF1, karyotype	Most comprehensive
MTSS	Transplant-specific	Allo-HSCT outcomes

Workflow

Input: Serial molecular testing, CBC, clinical parameters.
Baseline Assessment: Calculate initial risk score.
Mutation Tracking: Monitor VAF trends over time.
Risk Recalculation: Update scores at each timepoint.
Progression Detection: Identify molecular/clinical progression.
Treatment Assessment: Evaluate response to therapy.
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 Type	Parameters	Frequency
Molecular	JAK2/CALR/MPL VAF, NGS panel	q3-6 months
CBC	Hb, WBC, platelets, blasts	Monthly
Clinical	Symptoms, spleen size	q3 months
Bone Marrow	Fibrosis grade, cytogenetics	q6-12 months

Output Components

Output	Description	Format
Risk Scores	DIPSS, MIPSS70 over time	.csv
VAF Trends	Mutation burden plots	.png
Progression Alert	Warning if criteria met	.json
Response Assessment	IWG-MRT criteria	.json
Transplant Timing	Recommendation if indicated	.json
Clone Evolution	New mutations, clonal shifts	.csv

Progression Criteria

Progression Type	Criteria	Action
Clinical	New symptoms, splenomegaly	Intensify therapy
Hematologic	Cytopenias, increased blasts	BMB, cytogenetics
Molecular	New high-risk mutations	Risk restaging
Fibrotic	Increased fibrosis grade	Consider transplant
Blast Phase	≥20% blasts	Urgent intervention

Response Criteria (IWG-MRT)

Response	Definition	Implications
Complete Remission	No disease manifestations	Excellent outcome
Partial Remission	>50% improvement	Good response
Clinical Improvement	Symptom/spleen improvement	Benefit
Stable Disease	No change	Observe
Progressive Disease	Progression criteria	Change 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

Therapy	Response Markers	Timeline
Ruxolitinib	Spleen, symptoms, JAK2 VAF	12-24 weeks
Fedratinib	Similar to ruxolitinib	24 weeks
Momelotinib	+ anemia improvement	24 weeks
Interferon	Molecular response, JAK2 VAF	12+ 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

Factor	Risk Increase	Management
Age >60	2-3x	Cytoreduction
Prior thrombosis	3-5x	Anticoagulation
JAK2 V617F	2x	Higher for homozygous
High WBC	1.5-2x	Control counts
CV risk factors	Additive	Aggressive management

Special Considerations

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

Transplant Indications

Indication	Criteria	Timing
High-Risk PMF	MIPSS70+ high/very high	Consider early
Blast Phase	≥20% blasts	Urgent if fit
Refractory Disease	Failed JAKi	Evaluate
Transfusion Dependence	RBC/platelet dependent	Factor in decision

Author

AI Group - Biomedical AI Platform

---name: mpn-progression-monitor-agentdescription: AI-powered myeloproliferative neoplasm monitoring for disease progression prediction, treatment response tracking, and transformation risk assessment in PV, ET, and myelofibrosis.---# MPN Progression Monitor AgentThe **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 Capabilities1. **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 Type | Driver Mutations | Progression Risk ||----------|------------------|------------------|| PV | JAK2 V617F (95%), JAK2 exon 12 | Fibrosis 10-15%, AML 2-5% || ET | JAK2 (55%), CALR (25%), MPL (5%) | Fibrosis 5-10%, AML 1-2% || Pre-PMF | Same as PMF | Variable || PMF | JAK2 (60%), CALR (25%), MPL (5%) | AML 10-20% |## High-Risk Mutations| Mutation | Impact | MF Association ||----------|--------|----------------|| ASXL1 | Adverse | Strong || SRSF2 | Adverse | Strong (PMF) || EZH2 | Adverse | Moderate || IDH1/2 | Adverse | Transformation || RUNX1 | Very Adverse | Transformation || TP53 | Very Adverse | Transformation || U2AF1 | Adverse | Moderate |## Risk Scores| Score | Components | Application ||-------|------------|-------------|| IPSS | Age, Hb, WBC, blasts, symptoms | PMF at diagnosis || DIPSS | Same, dynamic | PMF follow-up || DIPSS+ | + karyotype, transfusion, platelets | PMF refined || MIPSS70 | Molecular markers | Transplant-age PMF || MIPSS70+ v2.0 | + U2AF1, karyotype | Most comprehensive || MTSS | Transplant-specific | Allo-HSCT outcomes |## Workflow1. **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**:```bashpython3 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 Type | Parameters | Frequency ||-----------|------------|-----------|| Molecular | JAK2/CALR/MPL VAF, NGS panel | q3-6 months || CBC | Hb, WBC, platelets, blasts | Monthly || Clinical | Symptoms, spleen size | q3 months || Bone Marrow | Fibrosis grade, cytogenetics | q6-12 months |## Output Components| Output | Description | Format ||--------|-------------|--------|| Risk Scores | DIPSS, MIPSS70 over time | .csv || VAF Trends | Mutation burden plots | .png || Progression Alert | Warning if criteria met | .json || Response Assessment | IWG-MRT criteria | .json || Transplant Timing | Recommendation if indicated | .json || Clone Evolution | New mutations, clonal shifts | .csv |## Progression Criteria| Progression Type | Criteria | Action ||------------------|----------|--------|| Clinical | New symptoms, splenomegaly | Intensify therapy || Hematologic | Cytopenias, increased blasts | BMB, cytogenetics || Molecular | New high-risk mutations | Risk restaging || Fibrotic | Increased fibrosis grade | Consider transplant || Blast Phase | ≥20% blasts | Urgent intervention |## Response Criteria (IWG-MRT)| Response | Definition | Implications ||----------|------------|--------------|| Complete Remission | No disease manifestations | Excellent outcome || Partial Remission | >50% improvement | Good response || Clinical Improvement | Symptom/spleen improvement | Benefit || Stable Disease | No change | Observe || Progressive Disease | Progression criteria | Change 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| Therapy | Response Markers | Timeline ||---------|------------------|----------|| Ruxolitinib | Spleen, symptoms, JAK2 VAF | 12-24 weeks || Fedratinib | Similar to ruxolitinib | 24 weeks || Momelotinib | + anemia improvement | 24 weeks || Interferon | Molecular response, JAK2 VAF | 12+ 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| Factor | Risk Increase | Management ||--------|---------------|------------|| Age >60 | 2-3x | Cytoreduction || Prior thrombosis | 3-5x | Anticoagulation || JAK2 V617F | 2x | Higher for homozygous || High WBC | 1.5-2x | Control counts || CV risk factors | Additive | Aggressive management |## Special Considerations1. **Triple-Negative MPN**: Different prognosis, consider other diagnoses2. **Cytogenetic Evolution**: High-risk signal, BMB follow-up3. **New Mutations**: May indicate disease evolution4. **Treatment Resistance**: Consider second-line or transplant5. **Quality of Life**: Balance treatment intensity## Transplant Indications| Indication | Criteria | Timing ||------------|----------|--------|| High-Risk PMF | MIPSS70+ high/very high | Consider early || Blast Phase | ≥20% blasts | Urgent if fit || Refractory Disease | Failed JAKi | Evaluate || Transfusion Dependence | RBC/platelet dependent | Factor in decision |## AuthorAI Group - Biomedical AI Platform

FridrichMethod/awesome-skills/tree/main/skills/mpn-progression-monitor-agent commit 40c70989e8

Frequently asked questions

npx skillmds@latest add fridrichmethod/mpn-progression-monitor-agent