Patient has anddometrial car inoma of lungs dmmr positive and msi stab

Patient has anddometrial car inoma of lungs dmmr positive and msi stable and . previously no radiation was given

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"endometrial carcinoma" AND "dMMR" AND "MSI-stable" AND treatment

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endometrial carcinoma dMMR MSI-stable discordant management immunotherapy 2024 2025

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"endometrial carcinoma" AND "dMMR" AND immunotherapy

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https://pmc.ncbi.nlm.nih.gov/articles/PMC11640124

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"endometrial cancer" AND "dMMR" AND "MSI discordant"

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dMMR MSI-stable discordant endometrial cancer pembrolizumab efficacy 2024

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PMID: 41371509

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Now I have a thorough picture. Let me compile the comprehensive answer.

Clinical Scenario Summary

Patient: Endometrial carcinoma (metastatic to lungs / stage IVB), dMMR by IHC but MSI-Stable by NGS - this is a recognized discordant phenotype. No prior radiation.

Step 1 - Understand the dMMR/MSI-Stable Discordance (Critical)

This is not a contradiction that invalidates immunotherapy eligibility. It is a well-characterized phenomenon. A 2026 study (Xi Y et al., Hum Pathol, PMID 41371509) analyzed 220 EC patients and found 9.5% of cases showed dMMR by IHC but MSS by NGS. The two main causes are:

Isolated MSH6 loss - MSH3 compensates functionally, so microsatellites remain apparently stable on PCR/NGS panels, but the repair system is genuinely deficient.
MLH1 promoter methylation - MLH1 protein is lost on IHC (dMMR) but microsatellite lengths remain within stable range on standard testing.

PCR-based MSI testing can reclassify some of these cases. The IHC-based dMMR result is now the FDA-recognized biomarker for pembrolizumab eligibility - not MSI status alone.

Step 2 - Overall Management Plan

First-Line Systemic Therapy (No Prior Chemo/Radiation)

The current standard of care for advanced/metastatic endometrial carcinoma (Stage IVB with lung metastases) is chemo-immunotherapy combination, with the most robust benefit in dMMR tumors:

Regimen	Trial	Key Outcome (dMMR subgroup)
Dostarlimab 500 mg Q3W + Carboplatin/Paclitaxel x6 cycles, then dostarlimab 1000 mg Q6W maintenance	RUBY / ENGOT-EN6	4-yr PFS ~49% vs ~19% placebo; OS benefit sustained; median OS not reached at 69 months follow-up (2026 data)
Pembrolizumab 200 mg Q3W + Carboplatin/Paclitaxel x6 cycles, then pembrolizumab maintenance	KEYNOTE-868	Significant PFS/OS benefit in dMMR group
Durvalumab + Carboplatin/Paclitaxel, then durvalumab ± Olaparib maintenance	DUO-E	PFS benefit, especially dMMR; Olaparib adds further benefit

FDA approvals (2024): All three regimens above are FDA-approved for primary advanced/recurrent endometrial carcinoma - pembrolizumab and dostarlimab approved regardless of MMR status, durvalumab specifically for dMMR.

For this patient with dMMR IHC: Any of the above regimens is appropriate. Given the dMMR biology, the immunotherapy benefit is expected to be substantial - RUBY 2026 data suggest potential curative intent in some dMMR patients.

Recommended First-Line Approach

Carboplatin AUC5 + Paclitaxel 175 mg/m² Q3W x 6 cycles + Dostarlimab or Pembrolizumab, followed by checkpoint inhibitor maintenance until progression or 2 years.

Regarding Radiation (No Prior RT)

Since lung metastases are present (distant stage IVB), radiation is generally NOT the primary modality. However:

Stereotactic body radiotherapy (SBRT) to individual lung metastases may be considered in oligometastatic disease (1-3 lesions) for local control or ablation of residual disease after systemic response.
Pelvic radiotherapy - if there is also local disease or risk of pelvic recurrence, can be sequenced with systemic therapy after completing chemotherapy cycles.
In dMMR tumors, immunotherapy alone has produced complete responses - RT can synergize via abscopal effect but is not routinely required upfront.

Step 3 - Additional Workup Recommended

Before starting treatment, ensure:

Re-test MSI by PCR (not NGS alone) - may reclassify to MSI-H and confirm immunotherapy eligibility under all criteria.
POLE exonuclease domain mutation testing - if POLE-mutated, ultra-mutator phenotype has extremely high immunotherapy response rates.
FIGO molecular classification: POLE mut > dMMR > TP53 mut > NSMP (guides prognosis and treatment intensity).
Baseline imaging: PET-CT or CT chest/abdomen/pelvis for full staging.
Lynch syndrome evaluation: dMMR EC warrants germline testing for MLH1/MSH2/MSH6/PMS2.

Step 4 - Subsequent Line Considerations (if 1st line fails)

Single-agent pembrolizumab or dostarlimab monotherapy is active in dMMR EC (ORR ~45% in KEYNOTE-158 cohort D).
Lenvatinib + pembrolizumab: FDA-approved for pMMR/non-MSI-H advanced EC after prior platinum - less relevant here but useful if discordance resolves to pMMR.
Nivolumab ± ipilimumab (dual checkpoint blockade): Ongoing trials for recurrent dMMR EC, including post-prior ICI with rechallenge criteria.

Bottom Line for This Patient

The dMMR status by IHC is the actionable biomarker, even with MSI-stable by NGS. This discordance is a known technical phenomenon, not a reason to withhold immunotherapy. First-line treatment should be carboplatin + paclitaxel + checkpoint inhibitor (dostarlimab or pembrolizumab), with maintenance immunotherapy. RUBY 2026 long-term data show unprecedented durable responses - some patients may be cured. Radiation (SBRT) can be considered for oligometastatic lung consolidation but is not the primary modality.

References:

Xi Y et al. Analysis of discordance between MMR and MSI testing in EC. Hum Pathol 2026. PMID 41371509
Powell MA et al. 4-yr survival outcomes with dostarlimab + chemo in dMMR/MSI-H EC - RUBY trial. Gynecol Oncol 2026.
O'Malley DM et al. Pembrolizumab in MSI-H/dMMR and non-MSI-H/non-dMMR advanced EC - KEYNOTE-158. Gynecol Oncol 2025. PMID 39847999
Riedinger CJ et al. Characterization of MMR/MSI-discordant endometrial cancers. Cancer 2024. DOI 10.1002/cncr.35030
Berek & Novak's Gynecology - dMMR/MSI-H pembrolizumab section.

Doctor has advised dostarlimab alone

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"dostarlimab" AND "endometrial cancer" AND monotherapy

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dostarlimab monotherapy dMMR endometrial cancer first line approval dose efficacy 2024 2025

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PMID: 37917058

Reading Article

PMID: 40382973

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Here is a complete breakdown of dostarlimab monotherapy for this patient:

Dostarlimab Monotherapy - What You Need to Know

Is This an Approved Indication?

Yes - with an important context. Dostarlimab monotherapy is FDA and EMA approved for dMMR endometrial cancer, but the approved indication specifies recurrent or advanced disease that has progressed on or after prior platinum-based chemotherapy.

The combination of dostarlimab + carboplatin/paclitaxel is the FDA/EMA-approved first-line regimen.
Dostarlimab monotherapy without chemotherapy is the approved option when the patient has already received prior platinum treatment.

For this patient (no prior radiation, and presumably no prior chemotherapy): If this is truly the first-line setting, the doctor may be choosing monotherapy due to:

Patient preference to avoid chemotherapy toxicity
Comorbidities making chemotherapy unsafe
The strong dMMR biology (immunotherapy alone can produce complete responses in dMMR tumors)
Participation in a clinical trial (NIHR 2025 briefing notes a phase III trial of dostarlimab monotherapy as first-line for dMMR is ongoing)

This is an off-label but clinically rational decision in dMMR patients given the high single-agent activity.

Dosing Regimen (GARNET Trial / Approved Schedule)

Phase	Dose	Frequency	Route
Loading (first 4 doses)	500 mg	Every 3 weeks (Q3W)	IV infusion
Maintenance (dose 5 onward)	1000 mg	Every 6 weeks (Q6W)	IV infusion

Infusion duration: 30 minutes. Treatment continues until disease progression, unacceptable toxicity, or completion of 2 years.

Efficacy Data - What to Expect

GARNET Trial (André T et al., JAMA Netw Open 2023, PMID 37917058) - dMMR solid tumors (141 of 327 patients had dMMR endometrial cancer):

Outcome	Result
Objective Response Rate (ORR)	44.0% (95% CI 38.6-49.6%)
Complete Response (CR)	~13%
Partial Response (PR)	~31%
Median Duration of Response	Not reached (range up to 47+ months)
Responses lasting ≥12 months	72.2% of responders
Median PFS	6.9 months; 40.6% PFS at 24 months
Median OS	Not reached (≥31.6 months)

DORA Real-World Study (Gallego A et al., Int J Gynecol Cancer 2025, PMID 40382973) - 125 evaluable dMMR/MSI-H EC patients in Spain:

Outcome	Result
ORR	53.6% (even higher than trial)
Complete Response	21.6%
Partial Response	32%
Median Time to Response	2.9 months
Response durability at 12 months	85%
Discontinuation due to toxicity	only 4.7%

Key message: Responses when they occur are deep and durable - many patients maintain response for years. Median duration of response has not been reached in multiple studies.

Monitoring During Treatment

Parameter	Frequency
Clinical assessment + labs (LFTs, TFTs, FBS, creatinine)	Every 3-6 weeks before each dose
CT chest/abdomen/pelvis imaging	Every 8-12 weeks to assess response
Thyroid function (TSH, FT4)	Every cycle - hypothyroidism is most common irAE
Blood glucose	Each visit - immune-mediated diabetes possible
Liver enzymes (ALT/AST)	Each cycle
Signs of pneumonitis	Symptom review every visit; low threshold for CT chest

Immune-Related Adverse Events (irAEs) to Watch

Most common (from GARNET):

Hypothyroidism - 6.9% (most frequent endocrine irAE; manage with levothyroxine, do not hold drug)
Elevated ALT/AST - 5.8% (hold for Grade 2+, steroids for Grade 3+)
Arthralgia - 4.7%
Fatigue, nausea, rash, pruritus - >20% any grade but usually grade 1-2
Pneumonitis - less common but serious; requires early CT evaluation

Management principle: For Grade 1 irAEs - continue with monitoring. For Grade 2 - hold dostarlimab, start prednisolone 1 mg/kg/day. For Grade 3-4 - permanently discontinue, high-dose IV methylprednisolone 1-2 mg/kg/day.

Expected Response Timeline

First assessment usually at 8-12 weeks (2-3 cycles)
Responses seen as early as 2.9 months (median time to response in DORA study)
Some patients show pseudoprogression (initial apparent enlargement due to immune infiltration) - do not stop early if patient is clinically stable
Durable complete responses have been reported - some patients may achieve long-term disease control

Summary for This Patient

The doctor's decision to use dostarlimab monotherapy is supported by strong clinical evidence for dMMR tumors. The dMMR IHC status is the key driver. Even in the discordant dMMR/MSI-stable situation, the IHC finding identifies a biologically immunotherapy-sensitive tumor. Response rates exceed 44-53% with median duration of response not reached. Toxicity is manageable and far less than platinum-based chemotherapy. The patient should have serial imaging at 8-12 weeks and proactive monitoring for thyroid and liver irAEs.

References:

André T et al. GARNET trial - dostarlimab monotherapy in dMMR solid tumors. JAMA Netw Open 2023. PMID 37917058
Gallego A et al. DORA real-world study. Int J Gynecol Cancer 2025. PMID 40382973
Goodman & Gilman's Pharmacological Basis of Therapeutics - Dostarlimab section
Harrison's Principles of Internal Medicine 22E (2025) - Checkpoint Inhibition Therapy

Doctor has said he will add tablet as well

Asking for Preferences

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"dostarlimab" AND "endometrial cancer" AND "olaparib" OR "niraparib" OR "lenvatinib"

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dostarlimab plus oral tablet endometrial cancer dMMR lenvatinib olaparib niraparib combination 2024 2025

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"dostarlimab" AND "niraparib" AND "endometrial cancer" RUBY

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"lenvatinib" AND "dostarlimab" AND "endometrial"

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RUBY Part 2 niraparib dostarlimab endometrial cancer results 2024 2025 dMMR

Now I have a clear picture. The tablet being added is almost certainly niraparib (Zejula) - a PARP inhibitor - based on the RUBY Part 2 trial data. Here is the full breakdown:

The Oral Tablet Addition: Most Likely Niraparib (Zejula)

In the context of dostarlimab for endometrial cancer, the tablet the doctor is referring to is almost certainly niraparib (Zejula) - an oral PARP inhibitor. This comes directly from the RUBY Part 2 trial, which is the landmark study establishing this exact combination.

What Is Niraparib and Why Add It?

Niraparib is a PARP inhibitor (poly-ADP ribose polymerase inhibitor) taken as an oral capsule. PARP enzymes help cancer cells repair their own DNA damage. By blocking PARP, niraparib causes DNA damage to accumulate inside cancer cells - pushing them toward cell death. In dMMR tumors (which already have impaired DNA repair), PARP inhibition creates a "double hit" on the cancer's DNA repair machinery, a concept called synthetic lethality.

The immunotherapy (dostarlimab) + PARP inhibitor (niraparib) combination also creates a synergistic immune effect: PARP inhibition increases the tumor mutational burden and immunogenicity of cancer cells, making them more visible to the T cells that dostarlimab has unleashed.

RUBY Part 2 Trial - The Key Evidence

The RUBY/ENGOT-EN6/GOG-3031 Phase III trial Part 2 studied:

Treatment arm: Dostarlimab + carboplatin/paclitaxel (6 cycles) → then dostarlimab + niraparib maintenance
Control arm: Placebo + carboplatin/paclitaxel → placebo maintenance

Outcome	Dostarlimab + Niraparib	Placebo	Benefit
Median PFS (overall)	14.5 months	8.3 months	+6.2 months
Risk reduction (HR)	HR 0.60	-	40% reduction in progression/death
PFS in pMMR/MSS	Significant benefit	-	Particularly meaningful in non-dMMR
PFS in dMMR	Benefit maintained	-	Additive to immunotherapy

(Results from ESMO Gynecologic Cancers Congress 2024 and Ann Oncol 2024)

Important note: The most striking additional benefit from adding niraparib is seen in the pMMR/MSS (non-immunotherapy-sensitive) group. For dMMR patients like this one, dostarlimab alone already performs exceptionally well, but niraparib may provide incremental further benefit.

Niraparib Dosing

Parameter	Detail
Starting dose	200 mg or 300 mg orally once daily (based on body weight and platelet count)
Weight-based dosing	<77 kg OR baseline platelets <150,000/μL → 200 mg/day; ≥77 kg AND platelets ≥150,000/μL → 300 mg/day
Timing	Same time every day, with or without food; best taken at bedtime to reduce nausea
Formulation	Capsules (100 mg each)
Duration	Maintenance - continue until progression or unacceptable toxicity

Niraparib Side Effects to Watch

Side Effect	Frequency	Management
Thrombocytopenia (low platelets)	Most common - ~30% any grade	Check CBC weekly for first month, then monthly; dose reduce if Grade 3-4
Anemia	~25%	Monitor CBC; transfuse if symptomatic
Neutropenia	~20%	Monitor CBC; hold/reduce dose if Grade 3-4
Nausea/vomiting	~40-50%	Bedtime dosing; antiemetics if needed
Fatigue	~30%	Supportive care
Hypertension	~20%	Monitor BP; antihypertensives if needed
Headache, dizziness	Common	Usually mild
MDS/AML	Rare (~1%)	Long-term risk; report unusual bruising or fatigue

Combined with dostarlimab irAEs: Grade 3+ adverse events and serious adverse events were approximately 36% higher in the combination arm vs placebo in RUBY Part 2. Patients need closer monitoring when on both agents.

CBC Monitoring Schedule for Niraparib

This is critical and mandatory:

Period	Monitoring
First month	CBC weekly
Month 2-3	CBC monthly
Ongoing	CBC monthly for duration of treatment

If platelets fall below 100,000/μL - hold niraparib and recheck in 1 week. Resume at reduced dose (step down 100 mg) when recovered.

Summary

The combination of dostarlimab (IV) + niraparib (oral tablet) is well-grounded in Phase III RUBY trial data. The tablet is almost certainly niraparib 200 mg or 300 mg daily. For this dMMR patient:

Dostarlimab attacks via immune checkpoint blockade
Niraparib attacks via PARP inhibition (synthetic lethality in DNA repair-deficient tumor)
Together they have additive/synergistic mechanisms
Weekly blood counts in the first month are essential to catch niraparib-related hematologic toxicity early

Please confirm with your oncologist whether the tablet prescribed is niraparib (Zejula), as lenvatinib (Lenvima) is another oral option used with different checkpoint inhibitors. The drug name will be on the prescription.

References:

RUBY Part 2: Mirza MR et al. Dostarlimab + carboplatin/paclitaxel → dostarlimab + niraparib in pA/rEC. Ann Oncol 2024. OncLive report
Powell MA et al. Niraparib maintenance with dostarlimab in EC. Int J Gynecol Cancer 2026. PMID 42391799
EMJ Advancements in Endometrial Cancer 2024 - RUBY Part 2 summary. Source

Ok give me aise effects monitoring schedule in pdf format

Reading File

Running Command

ls -la /home/daytona/workspace/ 2>/dev/null || mkdir -p /home/daytona/workspace …

Running Command

mkdir -p /home/daytona/workspace/endometrial-ca && python3 -c "from reportlab.li…

Writing File

~/endometrial-ca/generate_monitoring_pdf.py

from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, KeepTogether
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT
from reportlab.lib.colors import HexColor
import datetime

OUTPUT = "/home/daytona/workspace/endometrial-ca/AE_Monitoring_Schedule.pdf"

doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    rightMargin=1.8*cm,
    leftMargin=1.8*cm,
    topMargin=2*cm,
    bottomMargin=2*cm
)

# ── Colours ──────────────────────────────────────────────────────────────────
DARK_BLUE   = HexColor("#1a3a5c")
MID_BLUE    = HexColor("#2563a8")
LIGHT_BLUE  = HexColor("#dbeafe")
TEAL        = HexColor("#0f766e")
LIGHT_TEAL  = HexColor("#ccfbf1")
ORANGE      = HexColor("#c2410c")
LIGHT_ORG   = HexColor("#ffedd5")
YELLOW_HDR  = HexColor("#fef9c3")
GREY_HDR    = HexColor("#f1f5f9")
WHITE       = colors.white
RED_ALERT   = HexColor("#dc2626")
GREEN_OK    = HexColor("#16a34a")

styles = getSampleStyleSheet()

title_style = ParagraphStyle(
    "Title", parent=styles["Normal"],
    fontSize=18, fontName="Helvetica-Bold",
    textColor=WHITE, alignment=TA_CENTER, spaceAfter=4
)
subtitle_style = ParagraphStyle(
    "Subtitle", parent=styles["Normal"],
    fontSize=10, fontName="Helvetica",
    textColor=HexColor("#bfdbfe"), alignment=TA_CENTER
)
section_style = ParagraphStyle(
    "Section", parent=styles["Normal"],
    fontSize=12, fontName="Helvetica-Bold",
    textColor=WHITE, alignment=TA_LEFT,
    spaceBefore=6, spaceAfter=4,
    leftIndent=6, leading=16
)
body_style = ParagraphStyle(
    "Body", parent=styles["Normal"],
    fontSize=8.5, fontName="Helvetica",
    textColor=HexColor("#1e293b"),
    leading=12, spaceAfter=2
)
bold_body = ParagraphStyle(
    "BoldBody", parent=styles["Normal"],
    fontSize=8.5, fontName="Helvetica-Bold",
    textColor=HexColor("#1e293b"), leading=12
)
cell_style = ParagraphStyle(
    "Cell", parent=styles["Normal"],
    fontSize=8, fontName="Helvetica",
    textColor=HexColor("#1e293b"), leading=11
)
cell_bold = ParagraphStyle(
    "CellBold", parent=styles["Normal"],
    fontSize=8, fontName="Helvetica-Bold",
    textColor=HexColor("#1e293b"), leading=11
)
red_cell = ParagraphStyle(
    "RedCell", parent=styles["Normal"],
    fontSize=8, fontName="Helvetica-Bold",
    textColor=RED_ALERT, leading=11
)
green_cell = ParagraphStyle(
    "GreenCell", parent=styles["Normal"],
    fontSize=8, fontName="Helvetica-Bold",
    textColor=GREEN_OK, leading=11
)
alert_style = ParagraphStyle(
    "Alert", parent=styles["Normal"],
    fontSize=8, fontName="Helvetica-Bold",
    textColor=ORANGE, leading=11
)

def section_header(text, bg=DARK_BLUE):
    data = [[Paragraph(text, section_style)]]
    tbl = Table(data, colWidths=[17.2*cm])
    tbl.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), bg),
        ("ROUNDEDCORNERS", [4,4,4,4]),
        ("TOPPADDING", (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING", (0,0), (-1,-1), 8),
    ]))
    return tbl

def make_table(headers, rows, col_widths, header_bg=MID_BLUE, alt_bg=LIGHT_BLUE):
    header_para_style = ParagraphStyle(
        "TH", parent=styles["Normal"],
        fontSize=8, fontName="Helvetica-Bold",
        textColor=WHITE, leading=11, alignment=TA_CENTER
    )
    data = [[Paragraph(h, header_para_style) for h in headers]]
    for row in rows:
        data.append([Paragraph(str(c), cell_style) if not isinstance(c, Paragraph) else c for c in row])

    tbl = Table(data, colWidths=col_widths, repeatRows=1)
    style_cmds = [
        ("BACKGROUND", (0,0), (-1,0), header_bg),
        ("GRID", (0,0), (-1,-1), 0.4, HexColor("#cbd5e1")),
        ("ROWBACKGROUNDS", (0,1), (-1,-1), [WHITE, GREY_HDR]),
        ("VALIGN", (0,0), (-1,-1), "TOP"),
        ("TOPPADDING", (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING", (0,0), (-1,-1), 5),
        ("RIGHTPADDING", (0,0), (-1,-1), 5),
    ]
    tbl.setStyle(TableStyle(style_cmds))
    return tbl

# ── Build Story ───────────────────────────────────────────────────────────────
story = []

# ── TITLE BANNER ─────────────────────────────────────────────────────────────
title_data = [[
    Paragraph("Adverse Effects &amp; Monitoring Schedule", title_style),
    Paragraph("Dostarlimab (IV) + Niraparib (Oral)<br/>Endometrial Carcinoma (dMMR) — Metastatic", subtitle_style)
]]
title_tbl = Table(title_data, colWidths=[17.2*cm])
title_tbl.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,-1), DARK_BLUE),
    ("TOPPADDING", (0,0), (-1,-1), 12),
    ("BOTTOMPADDING", (0,0), (-1,-1), 12),
    ("LEFTPADDING", (0,0), (-1,-1), 10),
    ("ROUNDEDCORNERS", [6,6,6,6]),
]))
story.append(title_tbl)
story.append(Spacer(1, 0.3*cm))

date_str = datetime.date.today().strftime("%d %B %Y")
story.append(Paragraph(f"<i>Generated: {date_str} | For clinical reference only — individualise based on patient status</i>",
    ParagraphStyle("Date", parent=styles["Normal"], fontSize=7.5, textColor=HexColor("#64748b"), alignment=TA_CENTER)))
story.append(Spacer(1, 0.4*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 1 — DOSING QUICK REFERENCE
# ══════════════════════════════════════════════════════════════════════════════
story.append(section_header("1.  Dosing Quick Reference"))
story.append(Spacer(1, 0.2*cm))

dosing_data = [
    ["Drug", "Dose", "Route", "Schedule", "Duration"],
    [Paragraph("<b>Dostarlimab</b>\n(Jemperli)", cell_bold),
     "500 mg (doses 1–4)\n1000 mg (dose 5+)",
     "IV infusion\n30 min",
     "Q3W × 4 doses\nthen Q6W",
     "Until progression\nor 2 years"],
    [Paragraph("<b>Niraparib</b>\n(Zejula)", cell_bold),
     Paragraph("<b>200 mg/day</b> if &lt;77 kg\nOR platelets &lt;150k\n<b>300 mg/day</b> if ≥77 kg\nAND platelets ≥150k", cell_style),
     "Oral capsules\n(100 mg each)",
     "Once daily\n(bedtime preferred)",
     "Maintenance until\nprogression"],
]
story.append(make_table(
    ["Drug", "Dose", "Route", "Schedule", "Duration"],
    dosing_data[1:],
    [3.2*cm, 4.2*cm, 3*cm, 3.3*cm, 3.5*cm],
    header_bg=MID_BLUE
))
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 2 — MONITORING SCHEDULE
# ══════════════════════════════════════════════════════════════════════════════
story.append(section_header("2.  Monitoring Schedule by Timepoint"))
story.append(Spacer(1, 0.2*cm))

monitoring_rows = [
    [Paragraph("<b>Baseline\n(Before Cycle 1)</b>", cell_bold),
     "CBC + differential, CMP (LFTs, creatinine, electrolytes), blood glucose, HbA1c, TSH + Free T4, cortisol (if indicated), ECHO/MUGA (cardiac), BP, ECOG performance status, CT chest/abdomen/pelvis, urinalysis, serum β-hCG (if fertile age), weight"],
    [Paragraph("<b>Week 1, 2, 3, 4\n(Every week,\nMonth 1)</b>", cell_bold),
     Paragraph("<b>CBC with differential WEEKLY</b> — critical for niraparib haematologic toxicity\nBlood pressure weekly\nSymptom review (fatigue, nausea, bruising, bleeding)", cell_style)],
    [Paragraph("<b>Each Dostarlimab\nCycle (Q3W or Q6W)</b>", cell_bold),
     "CBC + differential, CMP (ALT/AST/bilirubin/creatinine), TSH, fasting glucose, BP\nSymptom screen for irAEs: cough/dyspnoea, diarrhoea, rash, joint pain, headache, visual changes\nECOG status"],
    [Paragraph("<b>Monthly\n(Months 2–6)</b>", cell_bold),
     "CBC monthly (niraparib), CMP monthly, TSH monthly for first 6 months\nBP monthly, weight monthly\nirAE symptom review"],
    [Paragraph("<b>Every 8–12 Weeks\n(Imaging)</b>", cell_bold),
     "CT chest/abdomen/pelvis (RECIST 1.1 assessment)\nNote: Do NOT stop treatment for apparent pseudoprogression if patient is clinically stable — repeat imaging in 4–6 weeks to confirm\nConsider PET-CT if ambiguous CT findings"],
    [Paragraph("<b>Every 3 Months\n(Ongoing)</b>", cell_bold),
     "CBC, CMP, TSH every 3 months after Month 6\nReview cumulative toxicity, dose modifications\nCardiac reassessment if symptoms develop\nAssess for secondary malignancy (long-term PARP inhibitor use: MDS/AML risk <1%)"],
    [Paragraph("<b>End of Treatment /\nAs Needed</b>", cell_bold),
     "Full panel + imaging at treatment discontinuation\nMonitor irAEs for ≥5 months after last dostarlimab dose (immune activation persists)\nLong-term thyroid function (hypothyroidism may be permanent)"],
]

story.append(make_table(
    ["Timepoint", "Tests / Actions Required"],
    monitoring_rows,
    [3.8*cm, 13.4*cm],
    header_bg=TEAL
))
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 3 — NIRAPARIB irAEs & DOSE MODIFICATIONS
# ══════════════════════════════════════════════════════════════════════════════
story.append(section_header("3.  Niraparib — Haematologic Toxicity & Dose Modifications", bg=TEAL))
story.append(Spacer(1, 0.2*cm))

nira_heme_rows = [
    [Paragraph("<b>Platelets</b>", cell_bold),
     "< 100,000/μL",
     Paragraph("<b>HOLD niraparib</b>\nRecheck CBC in 1 week", red_cell),
     Paragraph("Resume at reduced dose (−100 mg/day) when ≥100,000/μL\nMax 2 dose reductions (300→200→100 mg)\nDiscontinue if unable to tolerate 100 mg", cell_style)],
    [Paragraph("<b>Neutropenia</b>", cell_bold),
     "ANC < 1000/μL (Grade 3–4)",
     Paragraph("<b>HOLD niraparib</b>\nG-CSF if indicated", red_cell),
     "Resume at reduced dose when ANC ≥1500/μL\nConsider G-CSF prophylaxis"],
    [Paragraph("<b>Anaemia</b>", cell_bold),
     "Hgb < 8 g/dL or symptomatic",
     Paragraph("<b>HOLD niraparib</b>\nTransfuse if symptomatic", red_cell),
     "Resume at reduced dose when Hgb ≥9 g/dL\nEPO agents may be considered"],
    [Paragraph("<b>Any Grade 3–4\nHaematologic</b>", cell_bold),
     "Persisting >28 days after hold",
     Paragraph("<b>DISCONTINUE niraparib</b>", red_cell),
     "Do not rechallenge; continue dostarlimab if tolerated"],
]

story.append(make_table(
    ["Parameter", "Trigger Value", "Immediate Action", "Dose Modification / Re-initiation"],
    nira_heme_rows,
    [2.8*cm, 3.2*cm, 4.2*cm, 7*cm],
    header_bg=TEAL
))
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 4 — DOSTARLIMAB irAE MANAGEMENT
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    section_header("4.  Dostarlimab — Immune-Related Adverse Events (irAEs)", bg=MID_BLUE),
    Spacer(1, 0.2*cm),
]))

irae_rows = [
    # [irAE, frequency, grade, action, steroid]
    [Paragraph("<b>Hypothyroidism</b>", cell_bold),
     "Most common\n~6.9%",
     Paragraph("Grade 1–2", cell_style),
     "Continue dostarlimab\nStart levothyroxine",
     "No steroids needed"],
    [Paragraph("<b>Hyperthyroidism /\nThyroiditis</b>", cell_bold),
     "Less common",
     Paragraph("Grade 1–2", cell_style),
     "Continue; beta-blocker for symptoms\nMay evolve to hypothyroidism",
     "Steroids if severe"],
    [Paragraph("<b>Pneumonitis</b>", cell_bold),
     "Uncommon but serious",
     Paragraph("Grade 1: Monitor\nGrade 2: <b>HOLD</b>\nGrade 3–4: <b>STOP</b>", cell_style),
     "CT chest immediately\nGrade 2: prednisolone 1–2 mg/kg/day\nGrade 3–4: IV methylprednisolone 1–2 mg/kg/day",
     "Grade 2+: steroids mandatory"],
    [Paragraph("<b>Hepatitis\n(↑ALT/AST)</b>", cell_bold),
     "~5.8%",
     Paragraph("Grade 1: Monitor\nGrade 2: <b>HOLD</b>\nGrade 3–4: <b>STOP</b>", cell_style),
     "Grade 2: prednisolone 0.5–1 mg/kg\nGrade 3–4: IV methylprednisolone 1–2 mg/kg\nAdd mycophenolate if no improvement in 3 days",
     "Grade 2+: steroids"],
    [Paragraph("<b>Colitis /\nDiarrhoea</b>", cell_bold),
     "Uncommon",
     Paragraph("Grade 1: Loperamide\nGrade 2: <b>HOLD</b>\nGrade 3–4: <b>STOP</b>", cell_style),
     "Rule out infection (C. diff, CMV)\nGrade 2+: prednisolone 1–2 mg/kg\nGrade 3–4: infliximab if steroid-refractory",
     "Grade 2+: steroids"],
    [Paragraph("<b>Immune-Mediated\nDiabetes</b>", cell_bold),
     "Rare",
     Paragraph("Check glucose\nevery cycle", cell_style),
     "Insulin therapy (often type 1 DM pattern)\nContinue dostarlimab with insulin management",
     "No steroids"],
    [Paragraph("<b>Adrenal\nInsufficiency</b>", cell_bold),
     "Rare",
     Paragraph("Check morning\ncortisol if fatigued", cell_style),
     "Hydrocortisone replacement\nContinue dostarlimab with hormone replacement",
     "Physiologic steroids only"],
    [Paragraph("<b>Arthralgia /\nArthritis</b>", cell_bold),
     "~4.7%",
     Paragraph("Grade 1–2: NSAIDs\nGrade 3: <b>HOLD</b>", cell_style),
     "Grade 2+: prednisolone 0.5–1 mg/kg\nRheumatology consult for Grade 3+",
     "Grade 2+: steroids"],
    [Paragraph("<b>Rash /\nDermatitis</b>", cell_bold),
     ">20% any grade",
     Paragraph("Grade 1–2: Topical\nGrade 3: <b>HOLD</b>", cell_style),
     "Topical steroids/emollients for Grade 1–2\nSystemic steroids Grade 3+\nDermatology if SJS/TEN suspected",
     "Grade 3+: steroids"],
]

story.append(make_table(
    ["irAE", "Frequency", "Grading / Trigger", "Management", "Steroids"],
    irae_rows,
    [2.6*cm, 2.2*cm, 3.2*cm, 5.8*cm, 3.4*cm],
    header_bg=MID_BLUE
))
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 5 — STEROID TAPERING PROTOCOL
# ══════════════════════════════════════════════════════════════════════════════
story.append(section_header("5.  Steroid Taper Protocol for Grade 2+ irAEs", bg=HexColor("#7c3aed")))
story.append(Spacer(1, 0.2*cm))

taper_rows = [
    ["Step 1", "Start prednisolone 1–2 mg/kg/day orally (or IV methylprednisolone for Grade 3–4)"],
    ["Step 2", "Maintain until improvement to Grade 1 or below (usually 1–2 weeks)"],
    ["Step 3", "Taper by 10 mg/week (or 10% total dose/week) over ≥4–6 weeks minimum"],
    ["Step 4", "Do NOT restart dostarlimab until ≤10 mg/day prednisolone equivalent"],
    ["Step 5", "Prophylactic PCP cover (co-trimoxazole) if >20 mg/day prednisolone for >4 weeks"],
    ["Caution", "Rapid tapering (< 4 weeks) associated with irAE flare — taper slowly"],
]

taper_tbl = Table(taper_rows, colWidths=[2.5*cm, 14.7*cm])
taper_tbl.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (0,-1), HexColor("#ede9fe")),
    ("BACKGROUND", (1,0), (1,-1), WHITE),
    ("ROWBACKGROUNDS", (1,0), (1,-1), [WHITE, GREY_HDR]),
    ("GRID", (0,0), (-1,-1), 0.4, HexColor("#cbd5e1")),
    ("FONTNAME", (0,0), (0,-1), "Helvetica-Bold"),
    ("FONTNAME", (1,0), (1,-1), "Helvetica"),
    ("FONTSIZE", (0,0), (-1,-1), 8),
    ("VALIGN", (0,0), (-1,-1), "TOP"),
    ("TOPPADDING", (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("LEFTPADDING", (0,0), (-1,-1), 6),
    ("TEXTCOLOR", (0,5), (0,5), ORANGE),
]))
story.append(taper_tbl)
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 6 — RED FLAG SYMPTOMS (PATIENT ALERT CARD)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    section_header("6.  Red Flag Symptoms — Seek Immediate Medical Attention", bg=HexColor("#b91c1c")),
    Spacer(1, 0.2*cm),
]))

red_flags = [
    ["🔴 Breathing difficulty or new dry cough", "→ Possible immune pneumonitis — URGENT CT chest"],
    ["🔴 Severe diarrhoea (>4 stools/day) or bloody stool", "→ Possible immune colitis — HOLD drug, steroids"],
    ["🔴 Yellow skin / eyes or dark urine", "→ Possible immune hepatitis — URGENT LFTs"],
    ["🔴 Severe headache, visual changes, confusion", "→ Possible hypophysitis or meningitis — URGENT MRI"],
    ["🔴 Unexplained bruising, bleeding, or petechiae", "→ Possible thrombocytopenia — URGENT CBC"],
    ["🔴 Extreme fatigue, dizziness, fainting", "→ Possible adrenal insufficiency — URGENT cortisol"],
    ["🔴 Chest pain or irregular heartbeat", "→ Possible immune myocarditis — URGENT ECG + troponin"],
    ["🔴 Fever > 38.5°C with low neutrophils", "→ Febrile neutropenia — URGENT FBC + blood cultures"],
]

rf_tbl = Table(red_flags, colWidths=[8.2*cm, 9*cm])
rf_tbl.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,-1), HexColor("#fff1f2")),
    ("GRID", (0,0), (-1,-1), 0.4, HexColor("#fca5a5")),
    ("FONTNAME", (0,0), (0,-1), "Helvetica-Bold"),
    ("FONTNAME", (1,0), (1,-1), "Helvetica"),
    ("FONTSIZE", (0,0), (-1,-1), 8),
    ("TEXTCOLOR", (0,0), (0,-1), HexColor("#b91c1c")),
    ("TEXTCOLOR", (1,0), (1,-1), HexColor("#1e293b")),
    ("TOPPADDING", (0,0), (-1,-1), 4),
    ("BOTTOMPADDING", (0,0), (-1,-1), 4),
    ("LEFTPADDING", (0,0), (-1,-1), 6),
    ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
]))
story.append(rf_tbl)
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 7 — NIRAPARIB NON-HAEM AEs
# ══════════════════════════════════════════════════════════════════════════════
story.append(section_header("7.  Niraparib — Non-Haematologic Adverse Effects", bg=TEAL))
story.append(Spacer(1, 0.2*cm))

nira_non_heme = [
    ["Nausea / Vomiting", "40–50%", "Take at bedtime; antiemetics (ondansetron, metoclopramide); usually improves after 1st month"],
    ["Fatigue", "~30%", "Supportive; exclude anaemia as cause; dose reduce if Grade 3"],
    ["Hypertension", "~20%", "Monitor BP weekly (Month 1), then each cycle; antihypertensives if BP >140/90 persistently"],
    ["Headache / Dizziness", "~15–20%", "Usually mild; analgesics; rule out CNS metastasis if new or severe"],
    ["Constipation", "~15%", "Fibre, hydration, laxatives"],
    ["Abdominal pain / Mucositis", "~10–15%", "Symptomatic; dose reduce if Grade 3"],
    ["MDS / AML", "<1% (long-term)", "Annual CBC; report unexplained cytopenias; bone marrow biopsy if suspected"],
    ["Secondary Primary Malignancy", "Rare", "Long-term surveillance; no cases of MDS/AML reported in RUBY Part 2"],
]

story.append(make_table(
    ["Side Effect", "Frequency", "Management"],
    nira_non_heme,
    [4.2*cm, 2.5*cm, 10.5*cm],
    header_bg=TEAL
))
story.append(Spacer(1, 0.5*cm))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION 8 — SUMMARY SCHEDULE AT A GLANCE
# ══════════════════════════════════════════════════════════════════════════════
story.append(section_header("8.  At-a-Glance Summary Monitoring Calendar"))
story.append(Spacer(1, 0.2*cm))

summary_rows = [
    [Paragraph("<b>Test</b>", cell_bold),
     Paragraph("<b>Wk 1–4\n(Weekly)</b>", cell_bold),
     Paragraph("<b>Each\nCycle</b>", cell_bold),
     Paragraph("<b>Monthly\n(Mo 2–6)</b>", cell_bold),
     Paragraph("<b>Every\n3 Mo</b>", cell_bold),
     Paragraph("<b>Every\n8–12 Wk</b>", cell_bold)],
    ["CBC + Differential",
     Paragraph("✅ Weekly", green_cell),
     Paragraph("✅", green_cell), Paragraph("✅", green_cell), Paragraph("✅", green_cell), "—"],
    ["LFTs (ALT/AST/Bili)", "—",
     Paragraph("✅", green_cell), Paragraph("✅", green_cell), Paragraph("✅", green_cell), "—"],
    ["Renal Function (Cr, eGFR)", "—",
     Paragraph("✅", green_cell), Paragraph("✅", green_cell), Paragraph("✅", green_cell), "—"],
    ["TSH + Free T4", "—",
     Paragraph("✅", green_cell), Paragraph("✅ (Mo 1–6)", green_cell), Paragraph("✅", green_cell), "—"],
    ["Fasting Blood Glucose", "—",
     Paragraph("✅", green_cell), "—", Paragraph("✅", green_cell), "—"],
    ["Blood Pressure", Paragraph("✅ Weekly", green_cell),
     Paragraph("✅", green_cell), Paragraph("✅", green_cell), "—", "—"],
    ["irAE Symptom Review", Paragraph("✅", green_cell),
     Paragraph("✅", green_cell), Paragraph("✅", green_cell), Paragraph("✅", green_cell), "—"],
    ["CT Chest/Abdomen/Pelvis", "—", "—", "—", "—",
     Paragraph("✅ RECIST", green_cell)],
    ["ECHO / Cardiac (if symptoms)", "—", "As needed", "—", "As needed", "—"],
]

summary_tbl = Table(summary_rows, colWidths=[4.5*cm, 2.5*cm, 2.2*cm, 2.8*cm, 2.2*cm, 3*cm])
summary_tbl.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,0), DARK_BLUE),
    ("TEXTCOLOR", (0,0), (-1,0), WHITE),
    ("GRID", (0,0), (-1,-1), 0.4, HexColor("#cbd5e1")),
    ("ROWBACKGROUNDS", (0,1), (-1,-1), [WHITE, GREY_HDR]),
    ("FONTNAME", (0,1), (0,-1), "Helvetica-Bold"),
    ("FONTSIZE", (0,0), (-1,-1), 8),
    ("ALIGN", (1,0), (-1,-1), "CENTER"),
    ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
    ("TOPPADDING", (0,0), (-1,-1), 4),
    ("BOTTOMPADDING", (0,0), (-1,-1), 4),
    ("LEFTPADDING", (0,0), (-1,-1), 5),
]))
story.append(summary_tbl)
story.append(Spacer(1, 0.5*cm))

# ── FOOTER NOTE ───────────────────────────────────────────────────────────────
footer_data = [[Paragraph(
    "<b>References:</b> GARNET trial (André T et al., JAMA Netw Open 2023); RUBY trial Parts 1 &amp; 2 "
    "(Mirza MR et al., NEJM 2023; Ann Oncol 2024); DORA real-world study (Gallego A et al., Int J Gynecol Cancer 2025); "
    "Niraparib prescribing information (GSK/Zejula); Xi Y et al. dMMR/MSS discordance, Hum Pathol 2026. "
    "This document is for clinical reference. Individual patient decisions should be guided by the treating oncologist.",
    ParagraphStyle("Footer", parent=styles["Normal"], fontSize=6.5, textColor=HexColor("#64748b"), leading=10)
)]]
footer_tbl = Table(footer_data, colWidths=[17.2*cm])
footer_tbl.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,-1), GREY_HDR),
    ("TOPPADDING", (0,0), (-1,-1), 6),
    ("BOTTOMPADDING", (0,0), (-1,-1), 6),
    ("LEFTPADDING", (0,0), (-1,-1), 8),
    ("RIGHTPADDING", (0,0), (-1,-1), 8),
]))
story.append(footer_tbl)

# ── BUILD ─────────────────────────────────────────────────────────────────────
doc.build(story)
print(f"PDF saved to: {OUTPUT}")

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