"aplastic anemia" AND treatment

aplastic anemia 2024 2025 latest clinical trials eltrombopag horse ATG HSCT guidelines

PMID: 34986284

PMID: 42047558

"aplastic anemia" AND pathophysiology AND "T cell"

"aplastic anemia" AND "bone marrow transplant" AND outcomes

PMID: 35491054

PMID: 38669341

aplastic anemia bone marrow biopsy histology hypocellular

mkdir -p /tmp/workspace/aplastic-anemia-ppt && ls /tmp/workspace/

mkdir -p /tmp/workspace/aplastic-anemia-ppt && cat > /tmp/workspace/aplastic-anemia-ppt/build_ppt.py << 'PYEOF' from pptx import Presentation from pptx.util import Inches, Pt, Emu from pptx.dml.color import RGBColor from pptx.enum.text import PP_ALIGN, MSO_ANCHOR from pptx.util import Inches, Pt import copy prs = Presentation() prs.slide_width = Inches(13.333) prs.slide_height = Inches(7.5) blank = prs.slide_layouts[6] # ─── Color Palette ─────────────────────────────────────────────── DARK_BG = RGBColor(0x0D, 0x1B, 0x2A) # deep navy ACCENT1 = RGBColor(0xE8, 0x3A, 0x3A) # red accent ACCENT2 = RGBColor(0x00, 0xC2, 0xFF) # electric blue GOLD = RGBColor(0xFF, 0xC8, 0x00) # gold WHITE = RGBColor(0xFF, 0xFF, 0xFF) LIGHT_GRAY = RGBColor(0xD0, 0xD8, 0xE8) MID_BLUE = RGBColor(0x1A, 0x3A, 0x5C) TEAL = RGBColor(0x00, 0x8B, 0x8B) GREEN = RGBColor(0x00, 0xC8, 0x7A) ORANGE = RGBColor(0xFF, 0x8C, 0x00) def add_rect(slide, x, y, w, h, fill_color, transparency=0): shape = slide.shapes.add_shape(1, Inches(x), Inches(y), Inches(w), Inches(h)) shape.fill.solid() shape.fill.fore_color.rgb = fill_color shape.line.fill.background() return shape def add_textbox(slide, text, x, y, w, h, font_size=18, bold=False, color=WHITE, align=PP_ALIGN.LEFT, italic=False, wrap=True): tb = slide.shapes.add_textbox(Inches(x), Inches(y), Inches(w), Inches(h)) tf = tb.text_frame tf.word_wrap = wrap tf.margin_left = Pt(0) tf.margin_right = Pt(0) tf.margin_top = Pt(2) tf.margin_bottom = Pt(2) p = tf.paragraphs[0] p.alignment = align run = p.add_run() run.text = text run.font.size = Pt(font_size) run.font.bold = bold run.font.italic = italic run.font.color.rgb = color run.font.name = "Calibri" return tb def add_multiline_tb(slide, lines, x, y, w, h, font_size=14, color=WHITE, bold_first=False, line_spacing=1.15): from pptx.util import Pt as PPt from pptx.oxml.ns import qn from lxml import etree tb = slide.shapes.add_textbox(Inches(x), Inches(y), Inches(w), Inches(h)) tf = tb.text_frame tf.word_wrap = True tf.margin_left = Pt(4) tf.margin_right = Pt(4) tf.margin_top = Pt(2) tf.margin_bottom = Pt(2) first = True for i, line in enumerate(lines): if i == 0: p = tf.paragraphs[0] else: p = tf.add_paragraph() p.alignment = PP_ALIGN.LEFT run = p.add_run() run.text = line run.font.size = PPt(font_size) run.font.color.rgb = color run.font.name = "Calibri" run.font.bold = (bold_first and first) first = False return tb def bg(slide): add_rect(slide, 0, 0, 13.333, 7.5, DARK_BG) def header_bar(slide, title, subtitle=None): add_rect(slide, 0, 0, 13.333, 1.1, MID_BLUE) add_rect(slide, 0, 1.05, 13.333, 0.07, ACCENT1) add_textbox(slide, title, 0.3, 0.08, 11, 0.7, font_size=28, bold=True, color=WHITE, align=PP_ALIGN.LEFT) if subtitle: add_textbox(slide, subtitle, 0.3, 0.72, 11, 0.35, font_size=13, bold=False, color=ACCENT2) def footer(slide, txt="DM Hematology | Aplastic Anemia | Advanced Review 2025"): add_rect(slide, 0, 7.2, 13.333, 0.3, MID_BLUE) add_textbox(slide, txt, 0.3, 7.22, 12, 0.25, font_size=9, color=LIGHT_GRAY, align=PP_ALIGN.LEFT) # ══════════════════════════════════════════════════════════════════ # SLIDE 1 – TITLE # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) add_rect(s, 0, 0, 4.5, 7.5, MID_BLUE) # left panel add_rect(s, 4.45, 0, 0.08, 7.5, ACCENT1) # divider # Left panel accent add_rect(s, 0.2, 2.5, 3.8, 0.06, GOLD) add_textbox(s, "DM HEMATOLOGY", 0.3, 0.5, 4, 0.5, font_size=13, bold=True, color=GOLD, align=PP_ALIGN.LEFT) add_textbox(s, "APLASTIC\nANEMIA", 0.3, 1.1, 4.1, 2.2, font_size=46, bold=True, color=WHITE, align=PP_ALIGN.LEFT) add_textbox(s, "Advanced Clinical Review", 0.3, 2.9, 4, 0.45, font_size=16, bold=False, color=ACCENT2, align=PP_ALIGN.LEFT) add_textbox(s, "Pathophysiology | Diagnosis | Management\nLatest Trials & Guidelines 2025", 0.3, 3.5, 4, 0.8, font_size=12, color=LIGHT_GRAY, align=PP_ALIGN.LEFT) add_textbox(s, "Harrison's 22E | Robbins 11E\nNEJM 2022 | Blood 2024 | NEJM Evidence 2026\nASH Draft Guidelines 2025", 0.3, 4.5, 4, 1.0, font_size=10, color=LIGHT_GRAY, italic=True) # Right panel – slide index boxes topics = [ ("01", "Definition & Epidemiology"), ("02", "Etiology & Classification"), ("03", "Pathophysiology (Detailed)"), ("04", "Immune Mechanisms"), ("05", "Clonal Evolution & PNH"), ("06", "Clinical Features"), ("07", "Diagnosis & Investigations"), ("08", "Severity Classification"), ("09", "Treatment Algorithm"), ("10", "IST + Eltrombopag – Trials"), ("11", "HSCT – Indications & Outcomes"), ("12", "Salvage Therapy"), ("13", "Supportive Care"), ("14", "Prognosis & Follow-up"), ] ystart = 0.25 for num, topic in topics: add_rect(s, 4.7, ystart, 0.5, 0.38, ACCENT1) add_textbox(s, num, 4.72, ystart+0.02, 0.46, 0.35, font_size=11, bold=True, color=WHITE, align=PP_ALIGN.CENTER) add_textbox(s, topic, 5.25, ystart+0.04, 7.8, 0.35, font_size=12, color=LIGHT_GRAY) ystart += 0.47 # ══════════════════════════════════════════════════════════════════ # SLIDE 2 – DEFINITION & EPIDEMIOLOGY # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Definition & Epidemiology", "Aplastic Anemia — Overview") footer(s) # Definition box add_rect(s, 0.3, 1.25, 8.2, 1.45, MID_BLUE) add_rect(s, 0.3, 1.25, 0.12, 1.45, ACCENT1) add_textbox(s, "DEFINITION", 0.55, 1.28, 4, 0.35, font_size=12, bold=True, color=GOLD) add_textbox(s, "Aplastic anemia (AA) is pancytopenia with bone marrow hypocellularity resulting from destruction or suppression " "of multipotent hematopoietic stem cells (HSCs), leading to bone marrow failure. The marrow is often virtually " "devoid of recognizable hematopoietic elements and replaced by fat cells.", 0.55, 1.62, 7.85, 1.0, font_size=13, color=LIGHT_GRAY, wrap=True) # Epidemiology epi = [ ("Incidence", "2–3 per million/year (Western); 4–7 per million/year (Asia — 2× higher)"), ("Peak Age", "Bimodal: 15–25 years and >60 years; slight male predominance in older group"), ("Geography", "Higher rates in East Asia (viral hepatitis, environmental exposures)"), ("Mortality", "Without treatment: median survival <1 year in severe AA; >80% 5-yr survival with HSCT/IST"), ("Relation to PNH", "20–30% of AA have PNH clone at diagnosis; frank PNH develops in ~5–10%"), ("Relation to MDS", "Clonal evolution to MDS/AML in ~10–15% of treated patients over 10 years"), ] y = 2.85 for label, val in epi: add_rect(s, 0.3, y, 2.2, 0.38, RGBColor(0x1E, 0x4A, 0x6E)) add_textbox(s, label, 0.35, y+0.04, 2.1, 0.32, font_size=11, bold=True, color=GOLD) add_textbox(s, val, 2.6, y+0.04, 10.5, 0.38, font_size=11, color=LIGHT_GRAY, wrap=True) y += 0.46 # Right side stat boxes for bx, by, val, lbl, col in [ (9.1, 1.3, "~4-7", "per million/yr\n(Asia)", ACCENT2), (11.0, 1.3, "2-3", "per million/yr\n(West)", GREEN), (9.1, 2.45, "~80%", "5-yr survival\nwith HSCT/IST", GOLD), (11.0, 2.45, "10-15%", "Clonal\nevolution", ORANGE), ]: add_rect(s, bx, by, 1.7, 0.95, MID_BLUE) add_textbox(s, val, bx, by+0.04, 1.7, 0.5, font_size=20, bold=True, color=col, align=PP_ALIGN.CENTER) add_textbox(s, lbl, bx, by+0.52, 1.7, 0.42, font_size=10, color=LIGHT_GRAY, align=PP_ALIGN.CENTER) # ══════════════════════════════════════════════════════════════════ # SLIDE 3 – ETIOLOGY & CLASSIFICATION # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Etiology & Classification", "Causes and Types of Aplastic Anemia") footer(s) # Two columns cols = [ ("ACQUIRED (Immune-Mediated) — 80–85%", ACCENT1, [ "• Idiopathic (~70% of acquired) — most common", "• Post-hepatitis (seronegative hepatitis — non-A, B, C, G)", "• Drugs: chloramphenicol, NSAIDs, carbamazepine, sulfonamides,\n gold, penicillamine, felbamate (dose-independent, idiosyncratic)", "• Toxins: benzene, organophosphates, radiation", "• Infections: EBV, CMV, parvovirus B19, HIV, hepatitis viruses", "• Pregnancy-associated (rare; may remit post-partum)", "• Thymoma-associated", "• PNH-related aplasia", ]), ("INHERITED / CONSTITUTIONAL — 15–20%", GREEN, [ "• Fanconi Anemia — FANC genes (FANCA most common); DNA repair", "• Dyskeratosis Congenita — DKC1, TERT, TERC; telomere biology", "• Shwachman-Diamond — SBDS gene; exocrine pancreatic insufficiency", "• Diamond-Blackfan Anemia — ribosomal protein genes (RPS19, etc.)", "• GATA2 deficiency — MDS/AML, lymphedema, immunodeficiency", "• RUNX1 familial platelet disorder", "• Telomere Biology Disorders (TBD) — present in adults", "• Severe Congenital Neutropenia (Kostmann)", ]), ] for ci, (title, col, items) in enumerate(cols): xo = 0.3 + ci * 6.5 add_rect(s, xo, 1.2, 6.2, 0.42, col) add_textbox(s, title, xo+0.1, 1.23, 6.0, 0.38, font_size=12, bold=True, color=WHITE) add_rect(s, xo, 1.62, 6.2, 5.4, MID_BLUE) yt = 1.7 for item in items: add_textbox(s, item, xo+0.15, yt, 5.9, 0.55, font_size=11, color=LIGHT_GRAY, wrap=True) yt += 0.57 # ══════════════════════════════════════════════════════════════════ # SLIDE 4 – PATHOPHYSIOLOGY OVERVIEW # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Pathophysiology — Overview", "Two Major Mechanisms of Marrow Failure") footer(s) add_textbox(s, "Two primary (non-mutually exclusive) mechanisms underlie acquired AA:", 0.3, 1.2, 12.8, 0.4, font_size=13, color=GOLD, bold=True) # Mech 1 add_rect(s, 0.25, 1.65, 6.1, 4.5, MID_BLUE) add_rect(s, 0.25, 1.65, 6.1, 0.42, ACCENT1) add_textbox(s, "MECHANISM 1 — Immune-Mediated Destruction", 0.35, 1.67, 5.9, 0.38, font_size=12, bold=True, color=WHITE) pts1 = [ "▶ Antigen-altered HSCs trigger CD4+ Th1 activation", "▶ Oligoclonal cytotoxic CD8+ T cells attack HSCs", "▶ IFN-γ and TNF-α upregulate Fas on HSCs → apoptosis", "▶ IL-2 drives T cell expansion; IL-6 mediates inflammation", "▶ Th17 cells elevated in severe/late disease", "▶ Effector memory CD8+ T cells dominant in severe disease", "▶ Regulatory T cells (Tregs) markedly reduced → loss of\n immune tolerance", "▶ Type I interferons polarize immune system toward Th1\n in early phase", "▶ Clonal expansion of virus-reactive T cells that cross-react\n with HSC antigens (molecular mimicry — Blood 2024)", "▶ Evidence: IST (ATG + CsA) restores hematopoiesis in 60–70%", ] yt = 2.17 for pt in pts1: add_textbox(s, pt, 0.4, yt, 5.85, 0.45, font_size=11, color=LIGHT_GRAY, wrap=True) yt += 0.43 # Mech 2 add_rect(s, 6.7, 1.65, 6.15, 4.5, MID_BLUE) add_rect(s, 6.7, 1.65, 6.15, 0.42, ACCENT2) add_textbox(s, "MECHANISM 2 — Intrinsic HSC Defects", 6.8, 1.67, 5.95, 0.38, font_size=12, bold=True, color=WHITE) pts2 = [ "▶ 5–10% of cases: germline TERT/TERC mutations (telomerase)", "▶ 50% of AA: abnormally short telomeres even without mutation", "▶ Short telomeres → premature HSC senescence & exhaustion", "▶ Telomere defects → neoantigen expression → T cell attack\n (links mechanisms 1 & 2)", "▶ PIGA gene mutations → GPI anchor deficiency → PNH clone", "▶ Somatic mutations (clonal hematopoiesis) found in 30% at\n baseline; rise to 55% at 6 months, 80% at 24 months\n (NEJM Evidence 2026, Kaya et al.)", "▶ CH driver genes: DNMT3A, TET2, ASXL1, U2AF1, SF3B1", "▶ Loss-of-function mutations rescue HSCs from immune attack\n via HLA class I downregulation (immune escape)", "▶ IBMFS germline mutations in adults: GATA2, RUNX1, ERCC6L2", ] yt = 2.17 for pt in pts2: add_textbox(s, pt, 6.85, yt, 5.85, 0.45, font_size=11, color=LIGHT_GRAY, wrap=True) yt += 0.43 # ══════════════════════════════════════════════════════════════════ # SLIDE 5 – DETAILED IMMUNE PATHOPHYSIOLOGY # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Detailed Immune Pathophysiology", "Cytotoxic T Cell–Mediated Destruction of HSCs") footer(s) # Flow diagram using colored boxes and arrows steps = [ (0.3, 1.35, "TRIGGER\nDrug / Viral infection /\nUnknown antigen", ORANGE), (3.0, 1.35, "ANTIGEN\nPRESENTATION\nHSC presents neoantigen\nvia HLA class II", ACCENT1), (5.7, 1.35, "CD4+ Th1\nACTIVATION\nIL-2 secretion\nT cell proliferation", ACCENT2), (8.4, 1.35, "OLIGOCLONAL\nCD8+ CTL\nExpansion and\nhoming to marrow", MID_BLUE), (11.1, 1.35, "HSC\nDESTRUCTION\nFas/FasL, perforin\ngranzyme B, IFN-γ", ACCENT1), ] for (bx, by, txt, col) in steps: add_rect(s, bx, by, 2.55, 1.05, col) add_textbox(s, txt, bx+0.08, by+0.05, 2.4, 0.95, font_size=10.5, bold=False, color=WHITE, align=PP_ALIGN.CENTER) # Arrows for ax in [2.6, 5.3, 8.0, 10.7]: add_textbox(s, "➤", ax+0.05, 1.75, 0.4, 0.4, font_size=14, bold=True, color=GOLD, align=PP_ALIGN.CENTER) # Cytokine roles add_rect(s, 0.3, 2.6, 12.7, 0.38, RGBColor(0x10, 0x28, 0x40)) add_textbox(s, "KEY CYTOKINES & MEDIATORS", 0.4, 2.62, 12.5, 0.35, font_size=12, bold=True, color=GOLD) cyto_data = [ ("IFN-γ", "Upregulates Fas on HSCs, triggers apoptosis; induces CXCL10 attracting more CTLs", ACCENT1), ("TNF-α", "Synergizes with IFN-γ for HSC apoptosis; NF-κB activation", ORANGE), ("IL-2", "Drives T cell expansion; secreted by Th1 cells", ACCENT2), ("Th17/IL-17", "Elevated in severe disease; promotes inflammation", GREEN), ("Type I IFNs", "Early phase polarization toward Th1; amplify immune attack", TEAL), ("Tregs (↓)", "CD4+CD25+FoxP3+ cells markedly reduced → loss of self-tolerance", ACCENT1), ] yt = 3.1 for i, (name, desc, col) in enumerate(cyto_data): xi = 0.3 if i % 2 == 0 else 6.7 yt2 = yt if i < 2 else (yt + 0.52 * ((i // 2) - (0 if i % 2 == 0 else 0))) # Simpler linear layout pass # Draw as table rows yt = 3.08 for name, desc, col in cyto_data: add_rect(s, 0.3, yt, 2.0, 0.41, col) add_textbox(s, name, 0.32, yt+0.04, 1.96, 0.34, font_size=12, bold=True, color=WHITE, align=PP_ALIGN.CENTER) add_textbox(s, desc, 2.4, yt+0.05, 10.55, 0.38, font_size=11, color=LIGHT_GRAY, wrap=True) yt += 0.47 # Molecular mimicry box add_rect(s, 0.3, 5.95, 12.7, 0.5, RGBColor(0x1A, 0x1A, 0x4A)) add_rect(s, 0.3, 5.95, 0.1, 0.5, GOLD) add_textbox(s, "2024 ADVANCE (Blood 2024 — Ben Hamza et al.): Virus-reactive T cells in AA cross-react with HSC antigens via " "MOLECULAR MIMICRY — providing direct mechanistic proof of immune-mediated HSC destruction triggered by viral infection.", 0.5, 5.97, 12.4, 0.46, font_size=10.5, color=GOLD, italic=True, wrap=True) # ══════════════════════════════════════════════════════════════════ # SLIDE 6 – CLONAL EVOLUTION, PNH, CH # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Clonal Evolution, PNH & Clonal Hematopoiesis", "The AA–MDS–PNH Continuum") footer(s) # PNH section add_rect(s, 0.3, 1.2, 6.0, 0.38, ACCENT2) add_textbox(s, "PNH CLONE IN APLASTIC ANEMIA", 0.4, 1.22, 5.8, 0.34, font_size=13, bold=True, color=WHITE) pnh_pts = [ "• PNH clone (PIGA mutation → GPI-AP deficiency) detectable in 20–30% of AA at diagnosis by flow cytometry", "• Small PNH clones in AA: PROTECTIVE — escape immune destruction (GPI-AP−HSCs not recognized by CTLs)", "• Frank hemolytic PNH develops in ~5–10% of recovered AA patients as clone expands", "• AA and PNH share HLA-DR2 association; both respond to IST", "• Eculizumab (C5 inhibitor) for hemolytic PNH; does NOT treat underlying AA", "• Regular PNH clone monitoring by flow cytometry every 6–12 months in recovered AA", ] yt = 1.65 for pt in pnh_pts: add_textbox(s, pt, 0.35, yt, 5.9, 0.41, font_size=11, color=LIGHT_GRAY, wrap=True) yt += 0.42 # Clonal hematopoiesis section add_rect(s, 6.6, 1.2, 6.4, 0.38, ORANGE) add_textbox(s, "CLONAL HEMATOPOIESIS (CH) IN AA — NEJM Evidence 2026", 6.7, 1.22, 6.2, 0.34, font_size=11.5, bold=True, color=WHITE) ch_pts = [ "• Phase 3 RACE trial (Kaya et al., NEJM Evidence 2026, PMID 42047558):", " – 170 patients; samples at baseline, 6 months, 24 months", " – Somatic mutations at baseline: 30% of patients", " – At 6 months: 55.3% | At 24 months: 79.6%", " – Mean mutations/patient: 0.4 → 1.2 → 2.5 over 24 months", "• Common CH genes: DNMT3A, TET2, ASXL1, U2AF1, SF3B1, JAK2", "• CH reflects survival & expansion of immune-escape HSC clones", "• Eltrombopag addition did NOT increase CH or malignant transformation", "• HLA class I loss mutations: most common immune-escape mechanism", "• CH with myeloid-driver genes (RUNX1, SETBP1, CSF3R) → higher\n risk MDS/AML evolution — requires close surveillance", "• Annual bone marrow biopsy + cytogenetics + NGS panel recommended", ] yt = 1.65 for pt in ch_pts: add_textbox(s, pt, 6.65, yt, 6.25, 0.41, font_size=10.5, color=LIGHT_GRAY, wrap=True) yt += 0.41 # MDS evolution box add_rect(s, 0.3, 5.95, 12.7, 0.5, RGBColor(0x3A, 0x10, 0x10)) add_rect(s, 0.3, 5.95, 0.1, 0.5, ACCENT1) add_textbox(s, "CLONAL EVOLUTION TO MDS/AML: ~10–15% over 10 years post-IST. Cytogenetic abnormalities: monosomy 7 (highest risk), trisomy 8, del(13q). " "Annual marrow surveillance + cytogenetics mandatory. Monosomy 7 detected → proceed to HSCT urgently.", 0.5, 5.97, 12.4, 0.46, font_size=10.5, color=LIGHT_GRAY, italic=False, wrap=True) # ══════════════════════════════════════════════════════════════════ # SLIDE 7 – CLINICAL FEATURES # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Clinical Features", "Presentation, Examination & Red Flag Signs") footer(s) # Three columns clincols = [ ("SYMPTOMS", ACCENT2, [ "Anemia Symptoms", "• Fatigue, weakness, dyspnea", "• Pallor, palpitations", "• Exercise intolerance", "", "Thrombocytopenia", "• Petechiae, ecchymoses", "• Mucosal bleeding (gum, nose)", "• Menorrhagia", "• GI/intracranial bleeding (severe)", "", "Neutropenia", "• Recurrent bacterial infections", "• Fever", "• Oral ulcers, perianal infections", "• Life-threatening sepsis", ]), ("EXAMINATION", GREEN, [ "Positive Findings", "• Pallor (mucous membranes)", "• Petechiae / purpura", "• Ecchymoses", "• Signs of infection", "", "ABSENT Findings (key negatives)", "• NO hepatosplenomegaly", "• NO lymphadenopathy", "• If splenomegaly → question AA dx", "", "Constitutional (IBMFS)", "• Short stature, café-au-lait spots (FA)", "• Nail dystrophy, leukoplakia (DC)", "• Thumb anomalies (FA)", "• Pigmentation abnormalities", ]), ("RED FLAGS / SPECIAL", ORANGE, [ "Preceding Events", "• Seronegative hepatitis 2–3 months\n before → post-hepatitis AA", "• Drug exposure history", "", "Pregnancy", "• AA in pregnancy → rare but serious", "• May remit post-partum", "", "Inherited Syndromes", "• Young age + family history", "• Chromosomal breakage test (DEB)\n positive → Fanconi anemia", "• Telomere length assay", "• Pulmonary fibrosis (TBD)", "", "PNH Symptoms", "• Hemoglobinuria, dark urine", ]), ] for ci, (title, col, items) in enumerate(clincols): xo = 0.3 + ci * 4.35 add_rect(s, xo, 1.2, 4.1, 0.38, col) add_textbox(s, title, xo+0.1, 1.22, 3.9, 0.35, font_size=13, bold=True, color=WHITE) add_rect(s, xo, 1.58, 4.1, 5.47, MID_BLUE) yt = 1.65 for item in items: bold = not item.startswith("•") and item != "" fc = GOLD if bold and item != "" else LIGHT_GRAY add_textbox(s, item, xo+0.12, yt, 3.9, 0.42, font_size=10.5, bold=bold, color=fc, wrap=True) yt += 0.38 # ══════════════════════════════════════════════════════════════════ # SLIDE 8 – DIAGNOSIS & INVESTIGATIONS # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Diagnosis & Investigations", "Mandatory Work-up for Bone Marrow Failure") footer(s) # Left column – tests add_rect(s, 0.3, 1.2, 6.0, 0.38, ACCENT1) add_textbox(s, "LABORATORY INVESTIGATIONS", 0.4, 1.22, 5.8, 0.35, font_size=13, bold=True, color=WHITE) tests = [ ("CBC + Differential", "Pancytopenia: ↓Hb, ↓WBC (neutropenia), ↓Platelets; MCV often elevated"), ("Reticulocyte Count", "Absolute reticulocyte count <20×10⁹/L — hallmark of hypoplastic marrow"), ("Peripheral Smear", "Normocytic (or macrocytic) normochromic anemia; no dysplasia; no blasts"), ("Bone Marrow Aspirate", "Hypocellular; fat cells predominate; few scattered lymphocytes/plasma cells"), ("Trephine Biopsy", "Gold standard: cellularity <25% (severe AA); <50% with <30% residual cells"), ("Cytogenetics (BM)", "Exclude MDS; del(7q), monosomy 7, trisomy 8 suggest MDS/evolution"), ("PNH Flow Cytometry", "GPI-AP on RBCs & granulocytes; FLAER assay; detect clones ≥0.1%"), ("Chromosomal Breakage", "DEB/MMC test for Fanconi anemia in young patients"), ("Telomere Length", "Flow-FISH or qPCR; short telomeres → TBD/DC; <1st %ile significant"), ("Genomic Panel (NGS)", "Germline + somatic mutations: TERT, TERC, DKC1, GATA2, DNMT3A, etc."), ] yt = 1.65 for test, desc in tests: add_rect(s, 0.3, yt, 2.5, 0.41, MID_BLUE) add_textbox(s, test, 0.35, yt+0.03, 2.4, 0.36, font_size=10.5, bold=True, color=ACCENT2) add_textbox(s, desc, 2.85, yt+0.04, 3.4, 0.38, font_size=10, color=LIGHT_GRAY, wrap=True) yt += 0.46 # Right column add_rect(s, 6.6, 1.2, 6.4, 0.38, ACCENT2) add_textbox(s, "ADDITIONAL WORK-UP", 6.7, 1.22, 6.2, 0.35, font_size=13, bold=True, color=WHITE) extra = [ ("Viral Serology", "Hepatitis A/B/C/E, EBV, CMV, HIV, parvovirus B19"), ("LFTs / Hepatitis panel", "Post-hepatitis AA; elevated transaminases may precede marrow failure"), ("Autoimmune screen", "ANA, anti-dsDNA (exclude SLE-related marrow failure)"), ("HLA Typing", "Patient + siblings — for potential HSCT; done early"), ("Serum B12/Folate", "Exclude megaloblastic anemia mimicking pancytopenia"), ("Renal Function", "Baseline before ATG/CsA; CsA is nephrotoxic"), ("Iron Studies + Ferritin", "Baseline; frequent transfusions → iron overload monitoring"), ("Chest X-ray / CT", "Exclude mediastinal mass (thymoma); infection work-up"), ("Echocardiogram", "Baseline cardiac function before ATG; pre-HSCT evaluation"), ("Pregnancy test", "All women of childbearing age before treatment"), ("Urine osmolality", "If PNH suspected; hemoglobinuria"), ("Family history + exam", "For IBMFS; siblings for donor search"), ] yt = 1.65 for test, desc in extra: add_rect(s, 6.6, yt, 2.5, 0.41, MID_BLUE) add_textbox(s, test, 6.65, yt+0.03, 2.4, 0.36, font_size=10.5, bold=True, color=GREEN) add_textbox(s, desc, 9.15, yt+0.04, 3.75, 0.38, font_size=10, color=LIGHT_GRAY, wrap=True) yt += 0.46 # ══════════════════════════════════════════════════════════════════ # SLIDE 9 – SEVERITY CLASSIFICATION # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Severity Classification", "Camitta Criteria & EBMT Refinements") footer(s) # Camitta criteria box add_rect(s, 0.3, 1.2, 12.7, 0.75, MID_BLUE) add_rect(s, 0.3, 1.2, 0.1, 0.75, GOLD) add_textbox(s, "CAMITTA CRITERIA — Requires: BM cellularity <25% (or <50% with <30% hematopoietic cells)", 0.5, 1.22, 12.4, 0.35, font_size=13, bold=True, color=GOLD) add_textbox(s, "+ At least 2 of: Neutrophils <0.5×10⁹/L | Platelets <20×10⁹/L | Reticulocytes <20×10⁹/L", 0.5, 1.57, 12.4, 0.35, font_size=12, color=LIGHT_GRAY) # Categories cats = [ ("MODERATE\n(mAA)", TEAL, "Criteria", "Cytopenia NOT meeting severe criteria\nBone marrow cellularity <50%", "Management", "Watch & wait if mild\nIST if transfusion dependent or symptomatic\nNo urgent HSCT"), ("SEVERE\n(SAA)", ORANGE, "Criteria", "BM cellularity <25%\n≥2 of: Neutrophils <0.5, Plt <20, Retic <20 (all ×10⁹/L)", "Management", "IMMEDIATE treatment\nHSCT if MSD available (age <50)\nIST + Eltrombopag if no MSD"), ("VERY SEVERE\n(vSAA)", ACCENT1, "Criteria", "Meets SAA criteria +\nNeutrophils <0.2×10⁹/L", "Management", "URGENT treatment\nHighest priority for HSCT\nIST triple therapy if no donor\nG-CSF use controversial"), ] for ci, (name, col, l1, v1, l2, v2) in enumerate(cats): xo = 0.3 + ci * 4.35 add_rect(s, xo, 2.1, 4.1, 0.65, col) add_textbox(s, name, xo+0.1, 2.12, 3.9, 0.6, font_size=15, bold=True, color=WHITE, align=PP_ALIGN.CENTER) add_rect(s, xo, 2.75, 4.1, 1.6, MID_BLUE) add_textbox(s, l1, xo+0.1, 2.8, 3.9, 0.3, font_size=11, bold=True, color=GOLD) add_textbox(s, v1, xo+0.1, 3.1, 3.9, 1.1, font_size=11, color=LIGHT_GRAY, wrap=True) add_rect(s, xo, 4.35, 4.1, 1.85, RGBColor(0x10, 0x28, 0x40)) add_textbox(s, l2, xo+0.1, 4.4, 3.9, 0.3, font_size=11, bold=True, color=ACCENT2) add_textbox(s, v2, xo+0.1, 4.7, 3.9, 1.4, font_size=11, color=LIGHT_GRAY, wrap=True) # Additional markers add_rect(s, 0.3, 6.3, 12.7, 0.75, RGBColor(0x0A, 0x20, 0x38)) add_textbox(s, "RISK FACTORS FOR POOR PROGNOSIS:", 0.45, 6.32, 3.5, 0.35, font_size=11, bold=True, color=GOLD) add_textbox(s, "Age >40 | vSAA | Monosomy 7 on cytogenetics | High transfusion burden pre-treatment | " "Concomitant PNH with large clone | Failure to respond to 2 courses of IST | " "Prior cytotoxic therapy | Presence of myeloid-driver CH mutations (RUNX1, SETBP1)", 3.9, 6.32, 9.1, 0.72, font_size=10.5, color=LIGHT_GRAY, wrap=True) # ══════════════════════════════════════════════════════════════════ # SLIDE 10 – TREATMENT ALGORITHM # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Treatment Algorithm — First-Line", "Decision Pathway for Newly Diagnosed AA") footer(s) # Top: Diagnosis box add_rect(s, 5.5, 1.2, 2.4, 0.5, GOLD) add_textbox(s, "NEWLY DIAGNOSED AA", 5.52, 1.22, 2.36, 0.46, font_size=12, bold=True, color=DARK_BG, align=PP_ALIGN.CENTER) add_textbox(s, "▼", 6.55, 1.72, 0.5, 0.3, font_size=14, bold=True, color=GOLD, align=PP_ALIGN.CENTER) # Eligibility add_rect(s, 4.4, 2.05, 4.6, 0.5, MID_BLUE) add_textbox(s, "Assess: Age | Performance Status | HLA typing | Donor availability", 4.45, 2.07, 4.5, 0.46, font_size=11, color=ACCENT2, align=PP_ALIGN.CENTER, wrap=True) # Two branches add_textbox(s, "◄ MSD available", 2.3, 2.65, 2.0, 0.35, font_size=11, bold=True, color=GREEN) add_textbox(s, "No MSD ►", 9.0, 2.65, 2.0, 0.35, font_size=11, bold=True, color=ORANGE) # Branch 1: HSCT add_rect(s, 0.3, 3.05, 5.8, 3.95, MID_BLUE) add_rect(s, 0.3, 3.05, 5.8, 0.42, GREEN) add_textbox(s, "MATCHED SIBLING DONOR (MSD) HSCT", 0.4, 3.07, 5.6, 0.38, font_size=12, bold=True, color=WHITE) hsct_pts = [ "• Age <40 (or up to 50 in good PS): FIRST-LINE therapy", "• Conditioning: Cy/ATG (young); Flu/Cy/ATG (older/alternative donor)", "• Cyclophosphamide 50 mg/kg × 4 days + horse ATG", "• GVHD prophylaxis: CsA ± methotrexate", "• Outcomes: 5-year OS ~85–90% (children), ~70–80% (adults)", "• MUD transplant: outcomes approach MSD; more GVHD", "• Haploidentical + PT-Cy: emerging; OS ~70% (EBMT 2024)", "• Cord blood: option for children without MSD", "• ASTCT 2024 guidelines: haploidentical HCT valid upfront\n option when MSD unavailable (Blood Adv 2025)", "• Avoid pre-transplant transfusions if possible", "• Minimize transfusion to prevent HLA sensitization", ] yt = 3.55 for pt in hsct_pts: add_textbox(s, pt, 0.4, yt, 5.6, 0.42, font_size=10.5, color=LIGHT_GRAY, wrap=True) yt += 0.38 # Branch 2: IST add_rect(s, 7.2, 3.05, 5.8, 3.95, MID_BLUE) add_rect(s, 7.2, 3.05, 5.8, 0.42, ORANGE) add_textbox(s, "IMMUNOSUPPRESSIVE THERAPY (IST) — TRIPLE THERAPY", 7.3, 3.07, 5.6, 0.38, font_size=11, bold=True, color=WHITE) ist_pts = [ "STANDARD REGIMEN (Harrison's 22E):", "• Horse ATG (hATG) 40 mg/kg/day × 4 days", "• Cyclosporine A (CsA): 6 mg/kg/day × 6 months,\n then taper slowly over 18 months", "• Eltrombopag 150 mg/day from Day 1 × 6 months\n (triple therapy)", "• Prednisolone 1 mg/kg/day × 2 weeks (ATG serum sickness)", "", "RESPONSE RATES (triple therapy):", "• Overall response at 6 months: 68–94%", "• Complete response at 3 months: 22%", "• Complete response at 6 months: 58%", "• 2-year event-free survival: 46%", ] yt = 3.55 for pt in ist_pts: bold = not pt.startswith("•") and pt != "" fc = GOLD if bold else LIGHT_GRAY add_textbox(s, pt, 7.3, yt, 5.6, 0.42, font_size=10.5, bold=bold, color=fc, wrap=True) yt += 0.38 # ══════════════════════════════════════════════════════════════════ # SLIDE 11 – KEY CLINICAL TRIALS # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Key Clinical Trials — IST & Eltrombopag", "Landmark Evidence Shaping Current Practice") footer(s) trials = [ { "trial": "RACE Trial — Phase 3 RCT", "ref": "Peffault de Latour et al. NEJM 2022 (PMID 34986284)", "col": ACCENT1, "design": "Multicenter RCT | 197 patients | hATG+CsA ± eltrombopag", "results": [ "Complete response at 3 months: 10% (IST) vs 22% (IST+EPAG) — OR 3.2 (p=0.01)", "Overall response at 6 months: 41% vs 68%", "Median time to first response: 8.8 months vs 3.0 months", "MDS transformation: 1 vs 2 patients (similar)", "Somatic mutations (CH): 29% → 66% (IST) vs 31% → 55% (IST+EPAG) at 6 months", "2-year EFS: 34% (IST) vs 46% (IST+EPAG)", ], "conclusion": "EPAG addition significantly improves rate, rapidity & depth of response without extra toxicity", }, { "trial": "NIH Cohort 3 — Phase 1/2", "ref": "Townsley et al. NEJM 2017; followed by phase 2 data 2020", "col": ACCENT2, "design": "Single-arm | hATG+CsA+EPAG from Day 1 × 6 months | 90 pts", "results": [ "Overall response at 6 months: 94% (Cohort 3) — best arm", "Complete response at 6 months: 58%", "Improved marrow cellularity and hematopoietic progenitors", "No increase in clonal evolution vs historical controls (15%)", "Established Day 1 EPAG start as optimal", ], "conclusion": "Day-1 eltrombopag + hATG + CsA is the standard-of-care IST regimen", }, { "trial": "CLONAL DYNAMICS — Phase 3 RACE subset", "ref": "Kaya et al. NEJM Evidence 2026 (PMID 42047558)", "col": GOLD, "design": "Longitudinal somatic mutation analysis | 170 pts | 31-gene & 291-gene NGS panels", "results": [ "CH at baseline: 30% → at 6 months: 55.3% → at 24 months: 79.6%", "Mean mutations/patient: 0.4 → 1.2 → 2.5 (baseline→6→24 months)", "EPAG did NOT increase CH prevalence vs IST alone", "CH reflects immune-escape expansion of surviving HSC clones", "HLA class I loss: dominant immune-escape mechanism identified", ], "conclusion": "CH is ubiquitous in AA post-treatment; EPAG does not worsen clonal risk", }, ] yt = 1.22 for t in trials: add_rect(s, 0.3, yt, 12.7, 0.38, t["col"]) add_textbox(s, f"{t['trial']} | {t['ref']}", 0.4, yt+0.02, 12.5, 0.34, font_size=11.5, bold=True, color=WHITE) yt += 0.38 add_rect(s, 0.3, yt, 12.7, 0.32, MID_BLUE) add_textbox(s, f"Design: {t['design']}", 0.4, yt+0.04, 12.5, 0.28, font_size=10.5, color=ACCENT2, italic=True) yt += 0.32 for r in t["results"]: add_textbox(s, f" • {r}", 0.4, yt, 12.3, 0.33, font_size=10.5, color=LIGHT_GRAY, wrap=True) yt += 0.33 add_rect(s, 0.3, yt, 12.7, 0.32, RGBColor(0x1A, 0x38, 0x1A)) add_textbox(s, f"✔ Conclusion: {t['conclusion']}", 0.4, yt+0.04, 12.5, 0.28, font_size=10.5, color=GREEN, bold=True) yt += 0.42 # ══════════════════════════════════════════════════════════════════ # SLIDE 12 – HSCT IN DETAIL # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Hematopoietic Stem Cell Transplantation (HSCT)", "Indications, Conditioning & Outcomes") footer(s) add_rect(s, 0.3, 1.2, 12.7, 5.85, MID_BLUE) sections = [ ("INDICATIONS", ACCENT2, [ "• SAA/vSAA age <40 with MSD: First-line therapy (preferred over IST)", "• SAA age 40–50 with MSD: Consider HSCT first-line (case-by-case)", "• Age <18 with SAA: HSCT strongly preferred (better outcomes, fewer late effects)", "• Failure of ≥1 course of IST: Proceed to HSCT regardless of age (MSD or MUD)", "• Clonal evolution (monosomy 7, MDS): URGENT HSCT", "• IBMFS (Fanconi, DC): Modified conditioning mandatory", ]), ("CONDITIONING REGIMENS", ORANGE, [ "• Standard (MSD, age <40): Cyclophosphamide 50 mg/kg × 4 days + hATG", "• Older/Alternative donor: Fludarabine-based (Flu/Cy/ATG) — reduced toxicity", "• Fanconi anemia: Reduced-intensity (no alkylating agents)", "• Post-transplant cyclophosphamide (PT-Cy): GVHD prevention in haplo-HCT", "• Avoid TBI in AA (increases late malignancy risk)", ]), ("DONOR TYPES & OUTCOMES", GREEN, [ "• MSD: 5-yr OS 85–90% (children); 70–80% (adults) — BEST outcomes", "• MUD (10/10 HLA): OS ~70–75%; more GVHD, more infections", "• Haploidentical + PT-Cy: OS ~70% (EBMT 2024); emerging evidence for upfront use", " – ASTCT 2024 Guidelines: haploidentical valid upfront when MSD unavailable", "• Cord blood: option for children <20 kg; engraftment slower", "• Meta-analysis haploidentical AA (PMID 37442821, Ann Hematol 2023): acceptable efficacy", ]), ("COMPLICATIONS", ACCENT1, [ "• Graft failure (5–10%): Higher with MUD, prior transfusions, HLA sensitization", "• Acute GVHD (grade III-IV): 15–25% MSD; 30–40% MUD", "• Chronic GVHD: 20–40%; higher in older patients", "• Infections: Bacterial, fungal (pre-engraftment); CMV/EBV (post-engraftment)", "• Late effects: Secondary malignancy (rare without TBI), infertility, endocrine dysfunction", ]), ] yt = 1.28 for title, col, pts in sections: add_rect(s, 0.35, yt, 12.6, 0.35, col) add_textbox(s, title, 0.45, yt+0.03, 12.4, 0.3, font_size=11.5, bold=True, color=WHITE) yt += 0.35 for pt in pts: add_textbox(s, pt, 0.45, yt, 12.4, 0.4, font_size=10.5, color=LIGHT_GRAY, wrap=True) yt += 0.37 yt += 0.07 # ══════════════════════════════════════════════════════════════════ # SLIDE 13 – SALVAGE & SECOND-LINE THERAPY # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Salvage & Second-Line Therapy", "Management of Relapsed / Refractory AA") footer(s) add_textbox(s, "DEFINITION OF TREATMENT FAILURE: No response at 3–6 months | Relapse after response | Cyclosporine-dependent disease", 0.3, 1.2, 12.7, 0.42, font_size=12, bold=True, color=GOLD, wrap=True) # Options table options = [ ("Repeat IST (2nd course ATG)", ACCENT2, "Rabbit ATG (rATG) + CsA + Eltrombopag\n" "• Use rATG if horse ATG given first (switch species)\n" "• Response rate: ~30–40% in relapsed/refractory\n" "• Horse ATG superior to rabbit ATG as first-line\n" "• May combine with eltrombopag even if used first-line"), ("Allogeneic HSCT (if not done)", GREEN, "MUD / Haploidentical / Cord blood\n" "• Preferred for all patients with HLA-matched donor after IST failure\n" "• OS ~70% with MUD after IST failure\n" "• Earlier referral = better outcome (avoid multiple IST courses)"), ("Eltrombopag Monotherapy", ORANGE, "For patients refractory/intolerant to IST:\n" "• 150 mg/day (40 mg/day if East Asian)\n" "• Response in 40–50% of refractory cases\n" "• Romiplostim: Case reports/small series show benefit (Rinsho Ketsueki 2025)"), ("Danazol", TEAL, "Androgen therapy for telomere biology disorders:\n" "• Mechanism: upregulates TERT expression\n" "• Can improve cytopenias; used in DC, TBD\n" "• Hepatotoxicity; virilization in women"), ("Cyclosporine taper optimization", MID_BLUE, "CsA-dependent patients:\n" "• Slow taper over years\n" "• Add mycophenolate mofetil or sirolimus\n" "• Monthly monitoring of CBC during taper"), ("Novel / Investigational", ACCENT1, "2025 frontiers:\n" "• ITK inhibitor (ibrutinib-like): murine model benefit (Cancer Immunol 2025, PMID 40299061)\n" "• JAK inhibitors: investigated in immune-mediated marrow failure\n" "• Single-cell immune profiling guiding targeted therapy (Nat Commun 2025, PMID 40447607)\n" "• Anti-CD52 (alemtuzumab): used in refractory cases"), ] yt = 1.75 for i, (name, col, desc) in enumerate(options): xi = 0.3 if i % 2 == 0 else 6.7 if i % 2 == 0 and i > 0: yt += 1.55 add_rect(s, xi, yt, 6.1, 0.38, col) add_textbox(s, name, xi+0.1, yt+0.03, 5.9, 0.34, font_size=12, bold=True, color=WHITE) add_rect(s, xi, yt+0.38, 6.1, 1.12, MID_BLUE) add_textbox(s, desc, xi+0.12, yt+0.42, 5.85, 1.06, font_size=10.5, color=LIGHT_GRAY, wrap=True) # ══════════════════════════════════════════════════════════════════ # SLIDE 14 – SUPPORTIVE CARE # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Supportive Care", "Management of Cytopenias & Complications") footer(s) supp_cols = [ ("TRANSFUSION SUPPORT", ACCENT2, [ "Red Cell Transfusions", "• Threshold: Hb <7–8 g/dL (or <9 if symptomatic/cardiac)", "• Use leukocyte-depleted, CMV-negative products", "• Irradiate all products (immunosuppressed patients)", "• Minimize pre-HSCT transfusions (HLA sensitization risk)", "", "Platelet Transfusions", "• Prophylactic threshold: Plt <10×10⁹/L", "• Plt <20 if fever/active bleeding", "• HLA-matched platelets if refractory", "", "Iron Chelation", "• Serum ferritin >2500 μg/L or >25–30 units pRBC", "• Oral: Deferasirox; SC: Deferoxamine", "• Monitor LFTs, renal function during chelation", ]), ("INFECTION PROPHYLAXIS", GREEN, [ "Bacterial Prophylaxis", "• Fluoroquinolone (ciprofloxacin/levofloxacin)\n when ANC <0.5×10⁹/L", "• Dental hygiene; avoid invasive procedures", "", "Fungal Prophylaxis", "• Fluconazole or posaconazole (on ATG/steroids)", "• Voriconazole for Aspergillus coverage in high-risk", "", "Viral Prophylaxis", "• Acyclovir/valacyclovir: HSV/VZV reactivation during IST", "• CMV monitoring post-HSCT (weekly PCR)", "• PCP (Pneumocystis) prophylaxis: TMP-SMX or dapsone", "", "Growth Factors", "• G-CSF: Controversial in AA (may drive clonal evolution)", "• Short-term G-CSF for severe infection only", ]), ("OTHER SUPPORTIVE MEASURES", ORANGE, [ "Avoidance Strategies", "• Stop all offending drugs/toxins", "• Avoid live vaccines during IST/HSCT", "• Avoid NSAIDs, antiplatelet agents", "• Protective isolation when ANC <0.2", "", "Gastrointestinal", "• Eltrombopag: take on empty stomach (metal chelation)", "• Anti-nausea: ondansetron during ATG infusion", "• Proton pump inhibitor during steroid course", "", "Hormonal/Fertility", "• OCP/hormonal therapy for menorrhagia", "• Fertility counseling before HSCT", "• Sperm banking pre-transplant", "", "Mental Health", "• Psychosocial support", "• Disease education for patients and families", ]), ] for ci, (title, col, items) in enumerate(supp_cols): xo = 0.3 + ci * 4.35 add_rect(s, xo, 1.2, 4.1, 0.38, col) add_textbox(s, title, xo+0.08, 1.22, 3.95, 0.35, font_size=12, bold=True, color=WHITE) add_rect(s, xo, 1.58, 4.1, 5.57, MID_BLUE) yt = 1.65 for item in items: bold = not item.startswith("•") and item != "" and not item.startswith(" ") fc = GOLD if bold else LIGHT_GRAY add_textbox(s, item, xo+0.1, yt, 3.92, 0.42, font_size=10.5, bold=bold, color=fc, wrap=True) yt += 0.37 # ══════════════════════════════════════════════════════════════════ # SLIDE 15 – PROGNOSIS, MONITORING & FUTURE # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) header_bar(s, "Prognosis, Monitoring & Future Directions", "Long-Term Outcomes & Emerging Therapies") footer(s) # Prognosis boxes progs = [ ("With HSCT\n(MSD, <40 yrs)", "85–90%\n5-year OS", GREEN), ("With IST\n(triple therapy)", "70–80%\noverall response", ACCENT2), ("Relapse rate\nafter IST", "30–40%\nover 5 years", ORANGE), ("Clonal evolution\nto MDS/AML", "10–15%\nat 10 years", ACCENT1), ("CsA-dependent\nremission", "~15–25%\nof responders", TEAL), ] for i, (lbl, val, col) in enumerate(progs): xi = 0.3 + i * 2.6 add_rect(s, xi, 1.2, 2.45, 1.15, col) add_textbox(s, val, xi, 1.22, 2.45, 0.65, font_size=20, bold=True, color=WHITE, align=PP_ALIGN.CENTER) add_textbox(s, lbl, xi, 1.87, 2.45, 0.45, font_size=10, color=WHITE, align=PP_ALIGN.CENTER) # Monitoring schedule add_rect(s, 0.3, 2.5, 6.0, 0.38, ACCENT2) add_textbox(s, "MONITORING SCHEDULE POST-TREATMENT", 0.4, 2.52, 5.8, 0.34, font_size=12, bold=True, color=WHITE) mon = [ ("CBC + retics", "Weekly during active IST; every 4–8 weeks when stable"), ("CsA levels", "Every 2 weeks until stable; trough 200–400 ng/mL"), ("Renal / LFTs", "Every 4–8 weeks on CsA; monthly during EPAG"), ("BM biopsy + cytogenetics", "At 3 months (response assessment); then annually"), ("PNH flow cytometry", "Every 6 months if clone detected; annually otherwise"), ("Ferritin + LFTs", "Every 3 months if on chelation; every 6 months otherwise"), ("NGS somatic panel", "At baseline; at 24 months if CH suspected"), ] yt = 2.95 for test, freq in mon: add_rect(s, 0.3, yt, 2.5, 0.38, MID_BLUE) add_textbox(s, test, 0.35, yt+0.04, 2.4, 0.32, font_size=10.5, bold=True, color=ACCENT2) add_textbox(s, freq, 2.85, yt+0.05, 3.4, 0.34, font_size=10.5, color=LIGHT_GRAY, wrap=True) yt += 0.42 # Future directions add_rect(s, 6.6, 2.5, 6.4, 0.38, GOLD) add_textbox(s, "FUTURE DIRECTIONS & NOVEL THERAPIES (2024–2026)", 6.7, 2.52, 6.2, 0.34, font_size=11.5, bold=True, color=DARK_BG) futures = [ ("Single-cell genomics", "Mapping autoimmune T cell landscape pre/post-IST at single-cell resolution (Nat Commun 2025, PMID 40447607) — enabling precise immunotherapy targeting"), ("IL-2-inducible T cell kinase (ITK) inhibitor", "Targeting ITK ameliorates immune-mediated AA in murine models — potential new immunotherapy approach (Cancer Immunol Immunother 2025, PMID 40299061)"), ("Molecular mimicry targeting", "Identifying specific viral antigens that trigger AA → antigen-specific tolerization strategies (Blood 2024, PMID 38277625)"), ("EPAG frontloading optimization", "Optimal dose/duration, alternate TPO-RA agents (avatrombopag, lusutrombopag) under evaluation in Phase 2 trials"), ("Gene therapy for IBMFS", "Lentiviral correction of FANCA, DKC1 in Fanconi/DC: early phase trials ongoing"), ("ASH 2025 Draft Guidelines", "Systematic guidance for PNH testing, IST regimens, pediatric protocols — full publication anticipated 2025"), ] yt = 2.95 for name, desc in futures: add_rect(s, 6.6, yt, 6.4, 0.38, MID_BLUE) add_rect(s, 6.6, yt, 0.08, 0.38, GOLD) add_textbox(s, name, 6.72, yt+0.03, 2.2, 0.34, font_size=10, bold=True, color=GOLD) add_textbox(s, desc, 8.95, yt+0.03, 4.0, 0.38, font_size=10, color=LIGHT_GRAY, wrap=True) yt += 0.42 # ══════════════════════════════════════════════════════════════════ # SLIDE 16 – SUMMARY # ══════════════════════════════════════════════════════════════════ s = prs.slides.add_slide(blank) bg(s) add_rect(s, 0, 0, 13.333, 7.5, DARK_BG) add_rect(s, 0, 0, 13.333, 0.08, ACCENT1) add_rect(s, 0, 7.42, 13.333, 0.08, ACCENT1) add_textbox(s, "KEY TAKE-HOME MESSAGES", 0.5, 0.2, 12.3, 0.6, font_size=26, bold=True, color=GOLD, align=PP_ALIGN.CENTER) msgs = [ (ACCENT1, "PATHOPHYSIOLOGY", "Oligoclonal CD8+ T cells destroy HSCs via IFN-γ/Fas-mediated apoptosis. " "Intrinsic stem cell defects (telomere shortening, somatic mutations) co-exist. " "Molecular mimicry between viral antigens and HSC antigens is now established (Blood 2024)."), (ACCENT2, "DIAGNOSIS", "Pancytopenia + hypocellular BM on trephine biopsy. " "Mandatory: PNH flow cytometry, chromosomal breakage test (young), telomere length, " "NGS germline/somatic panel, HLA typing."), (GREEN, "FIRST-LINE TREATMENT", "MSD HSCT for age <40 with donor. " "Triple IST (hATG + CsA + Eltrombopag from Day 1) for all others — 68–94% overall response. " "RACE Trial 2022 establishes EPAG as standard. Harrison's 22E endorses 'triple therapy'."), (ORANGE, "TRIALS & EVIDENCE", "RACE Trial (NEJM 2022): EPAG triples CR rate at 3 months. " "NEJM Evidence 2026: CH ubiquitous post-AA, EPAG does not increase clonal risk. " "ASTCT 2024: Haploidentical HSCT is a valid upfront option without MSD."), (GOLD, "SURVEILLANCE", "Annual BM biopsy + cytogenetics + NGS mandatory. " "Monitor PNH clone q6–12 months. " "Monosomy 7 → urgent HSCT. 10–15% clonal evolution to MDS/AML over 10 years."), ] yt = 0.95 for col, title, msg in msgs: add_rect(s, 0.4, yt, 1.5, 0.75, col) add_textbox(s, title, 0.41, yt+0.1, 1.48, 0.6, font_size=11, bold=True, color=WHITE, align=PP_ALIGN.CENTER) add_rect(s, 1.9, yt, 11.0, 0.75, MID_BLUE) add_textbox(s, msg, 2.0, yt+0.08, 10.8, 0.65, font_size=11, color=LIGHT_GRAY, wrap=True) yt += 0.83 add_textbox(s, "Sources: Harrison's Principles of Internal Medicine 22E (2025) | Robbins Basic Pathology 11E | " "NEJM 2022 (PMID 34986284) | NEJM Evidence 2026 (PMID 42047558) | " "Blood Adv 2024 (PMID 38669341) | ASH Draft Guidelines 2025 | ASTCT 2024", 0.4, 7.0, 12.5, 0.38, font_size=9, color=LIGHT_GRAY, italic=True, wrap=True) # Save out_path = "/tmp/workspace/aplastic-anemia-ppt/Aplastic_Anemia_DM_Hematology_Advanced.pptx" prs.save(out_path) print(f"Saved: {out_path}") print(f"Slides: {len(prs.slides)}") PYEOF echo "Script written"

cd /tmp/workspace/aplastic-anemia-ppt && python build_ppt.py 2>&1