from docx import Document
from docx.shared import Pt, Inches, RGBColor
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.oxml.ns import qn
from docx.oxml import OxmlElement
import copy

doc = Document()

# ── Page margins ──────────────────────────────────────────────────────────────
for section in doc.sections:
    section.top_margin    = Inches(1.0)
    section.bottom_margin = Inches(1.0)
    section.left_margin   = Inches(1.25)
    section.right_margin  = Inches(1.0)

# ── Global font ───────────────────────────────────────────────────────────────
normal_style = doc.styles["Normal"]
normal_style.font.name = "Times New Roman"
normal_style.font.size = Pt(12)

# ── Helpers ───────────────────────────────────────────────────────────────────
def add_centered(text, bold=False, size=14, space_before=0, space_after=6):
    p = doc.add_paragraph()
    p.alignment = WD_ALIGN_PARAGRAPH.CENTER
    p.paragraph_format.space_before = Pt(space_before)
    p.paragraph_format.space_after  = Pt(space_after)
    run = p.add_run(text)
    run.bold      = bold
    run.font.name = "Times New Roman"
    run.font.size = Pt(size)
    return p

def add_heading_style(text, level=1):
    p = doc.add_heading(text, level=level)
    p.alignment = WD_ALIGN_PARAGRAPH.LEFT
    for run in p.runs:
        run.font.name = "Times New Roman"
    return p

def add_body(text, bold=False, indent=0):
    p = doc.add_paragraph()
    p.paragraph_format.left_indent   = Inches(indent)
    p.paragraph_format.space_after   = Pt(4)
    run = p.add_run(text)
    run.bold      = bold
    run.font.name = "Times New Roman"
    run.font.size = Pt(12)
    return p

def add_checkbox_item(label, indent=0.3):
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(indent)
    p.paragraph_format.space_after  = Pt(3)
    run = p.add_run(f"☐  {label}")
    run.font.name = "Times New Roman"
    run.font.size = Pt(12)
    return p

def add_fill_line(label, indent=0):
    p = doc.add_paragraph()
    p.paragraph_format.left_indent = Inches(indent)
    p.paragraph_format.space_after  = Pt(4)
    r1 = p.add_run(f"{label}: ")
    r1.bold      = True
    r1.font.name = "Times New Roman"
    r1.font.size = Pt(12)
    r2 = p.add_run("_" * 45)
    r2.font.name = "Times New Roman"
    r2.font.size = Pt(12)
    return p

def add_table(headers, rows=3):
    col_n = len(headers)
    tbl = doc.add_table(rows=rows + 1, cols=col_n)
    tbl.style = "Table Grid"
    hdr_row = tbl.rows[0]
    for i, h in enumerate(headers):
        cell = hdr_row.cells[i]
        cell.text = h
        for para in cell.paragraphs:
            for run in para.runs:
                run.bold = True
                run.font.name = "Times New Roman"
                run.font.size = Pt(11)
    for row in tbl.rows[1:]:
        for cell in row.cells:
            cell.text = ""
    return tbl

def page_break():
    doc.add_page_break()

# ══════════════════════════════════════════════════════════════════════════════
# PAGE 1  –  COVER PAGE
# ══════════════════════════════════════════════════════════════════════════════
add_centered("", size=12)
add_centered(
    '"IMMUNOHISTOCHEMICAL EXPRESSION OF PDL2 AND Ki67\n'
    'IN PREMALIGNANT LESIONS AND TUMOR-FREE SURGICAL MARGINS\n'
    'OF ORAL SQUAMOUS CELL CARCINOMA AND THEIR CORRELATION WITH\n'
    'CLINICOPATHOLOGICAL PARAMETERS"',
    bold=True, size=14, space_before=24, space_after=12
)
add_centered("By:", bold=False, size=12, space_after=4)
add_centered("Proforma", bold=True, size=13, space_after=4)
add_centered("Submitted to", bold=False, size=12, space_after=4)

# Blank name field
p = doc.add_paragraph()
p.alignment = WD_ALIGN_PARAGRAPH.CENTER
r = p.add_run("DR. ___________________________")
r.bold = True; r.font.size = Pt(12); r.font.name = "Times New Roman"

add_centered("", size=12)
add_centered("King George's Medical University,", bold=False, size=12)
add_centered("Lucknow", bold=False, size=12)
add_centered("for the degree of", bold=False, size=12)
add_centered("M.D.", bold=True, size=13)
add_centered("(PATHOLOGY)", bold=True, size=13)
add_centered("", size=12)
add_centered("DEPARTMENT OF PATHOLOGY,", bold=True, size=12)
add_centered("KING GEORGE'S MEDICAL UNIVERSITY,", bold=True, size=12)
add_centered("LUCKNOW-226003 (U.P.) INDIA", bold=True, size=12)
add_centered("JUNE  2026", bold=True, size=12, space_before=18)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# PAGE 2  –  COVER LETTER
# ══════════════════════════════════════════════════════════════════════════════
add_body("To,")
add_body("The Dean,")
add_body("Faculty of Medicine,")
add_body("King George's Medical University,")
add_body("Lucknow")
add_body("")
add_body("Through Proper Channel")
add_body("")
add_body("Subject: Request for submission of thesis Proforma for M.D. (PATHOLOGY)", bold=True)
add_body("")
add_body("Respected Sir/Madam,")
add_body("")
p = doc.add_paragraph()
p.paragraph_format.space_after = Pt(6)
r = p.add_run(
    'I humbly request you to have my thesis entitled '
    '"IMMUNOHISTOCHEMICAL EXPRESSION OF PDL2 AND Ki67 IN PREMALIGNANT LESIONS '
    'AND TUMOR-FREE SURGICAL MARGINS OF ORAL SQUAMOUS CELL CARCINOMA AND THEIR '
    'CORRELATION WITH CLINICOPATHOLOGICAL PARAMETERS" '
)
r.font.name = "Times New Roman"; r.font.size = Pt(12)
r2 = p.add_run(
    "registered for the MD (PATHOLOGY) examination of King George's Medical University, "
    "Lucknow to be held in 2028."
)
r2.font.name = "Times New Roman"; r2.font.size = Pt(12)

add_body(
    "The necessary particulars and proforma along with recommendations of Chief Supervisor and "
    "Co-supervisor are being submitted herewith for necessary action."
)
add_body("")
add_body("Thanking You,")
add_body("Yours obediently,")
add_body("")
add_body("")
add_body("(DR. ___________________________)")
add_body("Junior Resident 1st Year")
add_body("Department of Pathology,")
add_body("KGMU, Lucknow.")
add_body("")

# Forwarded by
p = doc.add_paragraph()
r = p.add_run("Forwarded and Recommended by:")
r.bold = True; r.font.name = "Times New Roman"; r.font.size = Pt(12)
add_body("")
add_body("(PROF. ___________________________)")
add_body("Professor & Head")
add_body("Department of Pathology,")
add_body("KGMU, Lucknow.")

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# PAGE 3  –  SUPERVISOR RECOMMENDATIONS
# ══════════════════════════════════════════════════════════════════════════════
add_centered("RECOMMENDATION OF CHIEF-SUPERVISOR", bold=True, size=13)
add_body("")
add_body("PROF. ___________________________")
add_body("MD, ___________________________")
add_body("Professor")
add_body("Department of Pathology,")
add_body("KGMU, Lucknow")
add_body("")
add_body("Signature: _________________________ Date: _____________")
add_body("")

add_centered("RECOMMENDATION OF CO-SUPERVISORS", bold=True, size=13)
add_body("")

# Two-column-like layout using tabs
for i in [1, 2]:
    add_body(f"PROF. ___________________________")
    add_body("MD / MS / ___________________________")
    add_body("Professor, Department of ___________________________")
    add_body("KGMU, Lucknow")
    add_body("Signature: _________________________ Date: _____________")
    add_body("")

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# PAGE 4  –  PROFORMA DETAILS
# ══════════════════════════════════════════════════════════════════════════════
add_centered("PROFORMA", bold=True, size=14, space_before=6, space_after=12)

fields = [
    ("Name", "DR. ___________________________"),
    ("Year & Month of Graduation", "___________________________"),
    ("University from which graduated", "___________________________"),
    ("Course to which admitted", "M.D. (Pathology)"),
    ("Date of admission", "___________________________"),
    ("Present Status", "Junior Resident I Year"),
    ("Department in which Subject of thesis falls", "Department of Pathology"),
    ("Title of thesis", '"IMMUNOHISTOCHEMICAL EXPRESSION OF PDL2 AND Ki67 IN\n'
                       'PREMALIGNANT LESIONS AND TUMOR-FREE SURGICAL MARGINS\n'
                       'OF ORAL SQUAMOUS CELL CARCINOMA AND THEIR CORRELATION\n'
                       'WITH CLINICOPATHOLOGICAL PARAMETERS"'),
    ("Brief resume of the work proposed to be undertaken", "Attached here-with"),
    ("Chief Supervisor", "PROF. ___________________________\nMD, ___________________________\nProfessor, Department of Pathology, KGMU, Lucknow"),
]

for label, val in fields:
    p = doc.add_paragraph()
    p.paragraph_format.space_after = Pt(6)
    r1 = p.add_run(f"{label}: ")
    r1.bold = True; r1.font.name = "Times New Roman"; r1.font.size = Pt(12)
    r2 = p.add_run(val)
    r2.font.name = "Times New Roman"; r2.font.size = Pt(12)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# BRIEF RESUME  –  INTRODUCTION
# ══════════════════════════════════════════════════════════════════════════════
add_heading_style("IMMUNOHISTOCHEMICAL EXPRESSION OF PDL2 AND Ki67 IN PREMALIGNANT LESIONS AND TUMOR-FREE SURGICAL MARGINS OF ORAL SQUAMOUS CELL CARCINOMA AND THEIR CORRELATION WITH CLINICOPATHOLOGICAL PARAMETERS", level=1)

add_heading_style("INTRODUCTION", level=2)

intro_paras = [
    ("Oral squamous cell carcinoma (OSCC) is among the most prevalent and aggressive malignancies of the oral cavity, "
     "ranking eighth in global cancer incidence with approximately 880,000 new cases and over 440,000 deaths annually "
     "(GLOBOCAN 2020). Despite advances in surgical, radiotherapeutic, and chemotherapeutic modalities, the overall "
     "5-year survival rate remains approximately 50%, largely owing to late-stage diagnosis, locoregional recurrence, "
     "and the biological complexity of the tumor microenvironment.[1,2]"),

    ("A significant proportion of OSCCs arise from oral potentially malignant disorders (OPMDs), which include oral "
     "leukoplakia, oral submucous fibrosis, oral lichen planus, and erythroplakia. These lesions affect approximately "
     "2.5% of the general population and carry a variable but noteworthy risk of malignant transformation. Early "
     "identification of molecular alterations within OPMDs and histologically negative surgical margins may allow "
     "timely intervention and reduce the burden of recurrent or progressive disease.[3,4]"),

    ("Tumor-free surgical margins are a cornerstone of curative intent surgery in OSCC. However, local recurrence "
     "occurs in a substantial proportion of patients even when margins are histologically clear, implicating "
     "subclinical molecular and immunological alterations in residual tissue - a phenomenon known as 'field "
     "cancerization'. Conventional histopathology is insufficient to detect these early molecular changes; "
     "immunohistochemistry (IHC) therefore plays an important supplementary role in characterizing the biological "
     "state of these margins.[5,6]"),

    ("Programmed cell death ligand-2 (PDL2 / PD-L2 / CD273 / B7-DC) is a second ligand of the programmed cell "
     "death receptor-1 (PD-1) axis. Like its homologue PD-L1, PDL2 mediates immune checkpoint signalling by "
     "suppressing T-cell proliferation, cytokine production, and cytotoxic activity, thereby enabling tumor cells "
     "to evade immune surveillance. While PD-L1 expression in OSCC and OPMDs has been reported in several studies, "
     "data on PDL2 expression in premalignant oral lesions and OSCC surgical margins remain sparse. Given that "
     "PDL2 has a higher affinity for PD-1 than PD-L1, its independent contribution to immune evasion in oral "
     "carcinogenesis warrants specific investigation.[7,8,9]"),

    ("Ki67 is a nuclear non-histone protein encoded by the MKI67 gene and is a well-established marker of "
     "cellular proliferative activity. It is expressed during all active phases of the cell cycle (G1, S, G2, and M) "
     "but is absent in resting (G0) cells. In oral pathology, Ki67 labelling index (Ki67-LI) has been correlated "
     "with the degree of epithelial dysplasia, histological grade of OSCC, lymph node metastasis, and overall "
     "prognosis. Elevated Ki67 expression in OPMDs may indicate accelerated progression toward malignancy, while "
     "its expression in tumor-free surgical margins may serve as a surrogate for residual proliferative activity "
     "and recurrence risk.[10,11]"),

    ("The simultaneous evaluation of PDL2 and Ki67 in OPMDs and OSCC tumor-free surgical margins - and their "
     "correlation with clinicopathological parameters such as type of OPMD, degree of epithelial dysplasia, "
     "histological grade, site, tobacco/alcohol habits, lymph node status, TNM stage, and recurrence - may "
     "yield a more nuanced picture of the immunological and proliferative landscape during oral carcinogenesis. "
     "Such data may also support the development of precision biomarker panels for risk stratification and "
     "patient selection for emerging immunotherapy strategies targeting the PD-1/PD-L axis.[12,13]"),

    ("In India, studies specifically addressing PDL2 expression in premalignant oral lesions and OSCC margins are "
     "virtually absent. The present study is therefore designed to fill this lacuna by performing IHC for PDL2 and "
     "Ki67 on archival and prospective tissue samples from OPMDs and tumor-free surgical margins of OSCC cases, "
     "and by correlating the expression data with detailed clinicopathological parameters."),
]

for para_text in intro_paras:
    p = doc.add_paragraph()
    p.paragraph_format.first_line_indent = Inches(0.4)
    p.paragraph_format.space_after       = Pt(6)
    r = p.add_run(para_text)
    r.font.name = "Times New Roman"; r.font.size = Pt(12)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# AIM AND OBJECTIVES
# ══════════════════════════════════════════════════════════════════════════════
add_heading_style("AIM AND OBJECTIVES", level=2)

add_body("Aim:", bold=True)
p = doc.add_paragraph()
p.paragraph_format.left_indent  = Inches(0.3)
p.paragraph_format.space_after  = Pt(8)
r = p.add_run(
    "To evaluate the immunohistochemical expression of PDL2 and Ki67 in premalignant lesions "
    "(OPMDs) and tumor-free surgical margins of oral squamous cell carcinoma, and to correlate "
    "their expression with clinicopathological parameters."
)
r.font.name = "Times New Roman"; r.font.size = Pt(12)

add_body("Objectives:", bold=True)

objectives = [
    "To assess PDL2 immunohistochemical expression in OPMDs, tumor-free surgical margins of OSCC, and normal oral mucosa (control).",
    "To assess Ki67 labelling index (Ki67-LI) in OPMDs, tumor-free surgical margins of OSCC, and normal oral mucosa (control).",
    "To compare PDL2 expression and Ki67-LI across OPMDs, OSCC tumor-free margins, and normal mucosa.",
    "To correlate PDL2 and Ki67 expression with clinicopathological parameters including:\n"
    "    a. Type and site of OPMD\n"
    "    b. Degree of epithelial dysplasia (WHO grading)\n"
    "    c. Risk habits (tobacco, betel quid, alcohol)\n"
    "    d. Primary tumor site and histological grade of OSCC\n"
    "    e. Depth of invasion, perineural invasion, and lymphovascular invasion\n"
    "    f. Lymph node metastasis and TNM/AJCC stage\n"
    "    g. Margin status (close vs. clear)",
    "To evaluate the association of PDL2 and Ki67 co-expression with clinicopathological parameters.",
    "To determine the association of PDL2 and Ki67 expression with disease recurrence and survival outcomes (overall survival and disease-free survival at 3 years, where data are available).",
]

for i, obj in enumerate(objectives, 1):
    p = doc.add_paragraph()
    p.paragraph_format.left_indent = Inches(0.3)
    p.paragraph_format.space_after  = Pt(5)
    r = p.add_run(f"{i}. {obj}")
    r.font.name = "Times New Roman"; r.font.size = Pt(12)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# MATERIAL AND METHODS
# ══════════════════════════════════════════════════════════════════════════════
add_heading_style("MATERIAL AND METHODS", level=2)

add_body("Study Setting:", bold=True)
add_body(
    "The study will be undertaken in the Department of Pathology, King George's Medical University (KGMU), "
    "Lucknow, in collaboration with the Department of Oral and Maxillofacial Surgery / Head and Neck Oncology, "
    "KGMU, after approval from the Institutional Ethics Committee."
)

add_body("Study Design:", bold=True)
add_body("Hospital-based combined retrospective and prospective cross-sectional observational study.")

add_body("Study Duration:", bold=True)
tbl = add_table(["Phase", "Study Type", "Period"], rows=2)
tbl.rows[1].cells[0].text = "Phase I"
tbl.rows[1].cells[1].text = "Retrospective"
tbl.rows[1].cells[2].text = "January 2023 to July 2026"
tbl.rows[2].cells[0].text = "Phase II"
tbl.rows[2].cells[1].text = "Prospective"
tbl.rows[2].cells[2].text = "August 2026 to December 2027"
doc.add_paragraph()

add_body("Sample Size:", bold=True)
p = doc.add_paragraph()
p.paragraph_format.left_indent = Inches(0.3)
p.paragraph_format.space_after  = Pt(6)
r = p.add_run(
    "The sample size was estimated using the formula for estimating a single proportion:\n\n"
    "        n = Z² × p × q / d²\n\n"
    "Where:\n"
    "  Z = 1.96 (95% confidence interval)\n"
    "  p = Expected prevalence of PDL2 positivity in OPMDs ≈ 40% (0.40), based on available PD-L1/PDL2 literature in oral precancerous lesions\n"
    "  q = 1 − p = 0.60\n"
    "  d = Absolute precision = 15% (0.15)\n\n"
    "  n = (1.96)² × 0.40 × 0.60 / (0.15)² ≈ 41\n\n"
    "Adding 20% for dropouts, a minimum of 50 cases per group (OPMDs and OSCC surgical margins) will be enrolled, "
    "with 20 cases of normal oral mucosa as control.\n"
    "Total sample: approximately 120 tissue samples."
)
r.font.name = "Times New Roman"; r.font.size = Pt(12)

doc.add_paragraph()
add_body("Groups:", bold=True)
groups = [
    "Group A – Oral potentially malignant disorders (OPMDs): n = 50",
    "Group B – Tumor-free surgical margins of OSCC: n = 50",
    "Group C – Normal oral mucosa (control): n = 20",
]
for g in groups:
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(0.3)
    r = p.add_run(g); r.font.name = "Times New Roman"; r.font.size = Pt(12)

doc.add_paragraph()
add_body("Inclusion Criteria:", bold=True)
inc = [
    "Patients aged ≥18 years with a histopathologically confirmed diagnosis of OPMD or OSCC.",
    "For Group A: Biopsy-confirmed OPMDs including leukoplakia, oral submucous fibrosis, oral lichen planus, erythroplakia, or erythroleukoplakia.",
    "For Group B: OSCC cases with histologically tumor-free surgical margins (all margins clear on H&E).",
    "For Group C: Normal oral mucosa from patients undergoing minor oral surgery (e.g., impaction removal) with no evidence of mucosal disease.",
    "Adequate formalin-fixed paraffin-embedded (FFPE) tissue with sufficient material for IHC.",
    "Patients providing written informed consent (for prospective arm).",
]
for item in inc:
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(0.3)
    r = p.add_run(item); r.font.name = "Times New Roman"; r.font.size = Pt(12)

doc.add_paragraph()
add_body("Exclusion Criteria:", bold=True)
exc = [
    "Recurrent OSCC or previously treated cases (radiotherapy/chemotherapy) for the retrospective arm.",
    "Histologically positive surgical margins.",
    "Variants of squamous cell carcinoma (e.g., verrucous, spindle cell, basaloid).",
    "Non-squamous malignancies of the oral cavity.",
    "Inadequately fixed, poorly preserved, or insufficient FFPE tissue.",
    "Patients lost to follow-up (for survival analysis sub-group).",
    "Patients not giving consent.",
]
for item in exc:
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(0.3)
    r = p.add_run(item); r.font.name = "Times New Roman"; r.font.size = Pt(12)

page_break()

# ── METHODS DETAIL ────────────────────────────────────────────────────────────
add_heading_style("METHODS", level=3)

add_body("Data Collection:", bold=True)
add_body(
    "A structured Case Record Form (CRF) will be used to collect demographic, clinical, radiological, "
    "operative, and histopathological data for each patient."
)

add_body("Tissue Processing:", bold=True)
tp_text = (
    "Archival FFPE blocks will be retrieved from departmental archives. For prospective cases, fresh tissue "
    "will be fixed in 10% neutral buffered formalin for 12-24 hours. Sections of 4 µm thickness will be "
    "cut on poly-L-lysine coated slides for IHC staining."
)
add_body(tp_text)

add_body("Histopathological Examination:", bold=True)
add_body(
    "Routine H&E sections will be reviewed by two pathologists independently for confirmation of diagnosis, "
    "degree of dysplasia (WHO grading), histological grade of OSCC, depth of invasion, pattern of invasion, "
    "perineural invasion (PNI), and lymphovascular invasion (LVI)."
)

add_body("Immunohistochemical Protocol – PDL2:", bold=True)
ihc_pdl2 = [
    "Antibody: Rabbit monoclonal anti-PDL2 antibody (clone: ___; supplier: ___; dilution: 1:___)",
    "Antigen retrieval: Heat-induced epitope retrieval (HIER) in sodium citrate buffer (0.01 M, pH 6.0) for 10 min.",
    "Endogenous peroxidase block: 3% H₂O₂ in methanol for 30 min.",
    "Primary antibody incubation: 90 min at room temperature in humidifying chamber.",
    "Detection: Universal Immuno-enzyme Polymer (HRP-polymer) method.",
    "Chromogen: 3,3'-diaminobenzidine (DAB).",
    "Counterstain: Mayer's hematoxylin.",
    "Positive control: Known PDL2-positive tumor tissue.",
    "Negative control: Sections incubated with PBS replacing primary antibody.",
    "Scoring: H-score (intensity [0-3] × percentage of positive cells [0-100]) and/or CPS method.",
]
for item in ihc_pdl2:
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(0.5)
    r = p.add_run(item); r.font.name = "Times New Roman"; r.font.size = Pt(12)

doc.add_paragraph()
add_body("Immunohistochemical Protocol – Ki67:", bold=True)
ihc_ki67 = [
    "Antibody: Mouse monoclonal anti-Ki67 antibody (clone MIB-1; supplier: ___; dilution: 1:___)",
    "Antigen retrieval: HIER in EDTA buffer (pH 8.0) or sodium citrate (pH 6.0) for 10 min.",
    "Endogenous peroxidase block: 3% H₂O₂ in methanol for 30 min.",
    "Primary antibody incubation: 60-90 min at room temperature.",
    "Detection: Universal Immuno-enzyme Polymer (HRP-polymer) method.",
    "Chromogen: DAB.",
    "Counterstain: Mayer's hematoxylin.",
    "Ki67 labelling index (Ki67-LI): Percentage of Ki67-positive nuclei per 1000 tumor/epithelial cells counted in hot-spot areas at 400× magnification.",
    "Positive control: Known Ki67-positive tissue (lymph node / tonsil).",
]
for item in ihc_ki67:
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(0.5)
    r = p.add_run(item); r.font.name = "Times New Roman"; r.font.size = Pt(12)

doc.add_paragraph()
add_body("Scoring and Interpretation:", bold=True)
score_items = [
    "PDL2 scoring: Tumour cells, lymphocytes, and macrophages will be evaluated. CPS = (PDL2-positive cells / total viable tumour cells) × 100. PDL2 H-score: intensity (0-3) × proportion (%). Cutoff for positivity: CPS ≥1 (low) and CPS ≥10 (high). Two blinded independent observers will evaluate; interobserver variability assessed by Cohen's κ.",
    "Ki67 scoring: Ki67-LI (%) = (number of Ki67-positive nuclei / total nuclei counted) × 100. Cutoff: Low (<20%) vs. High (≥20%) proliferative index. Two independent observers; mean Ki67-LI used for analysis.",
]
for item in score_items:
    p = doc.add_paragraph(style="List Bullet")
    p.paragraph_format.left_indent = Inches(0.5)
    r = p.add_run(item); r.font.name = "Times New Roman"; r.font.size = Pt(12)

doc.add_paragraph()
add_body("Statistical Analysis:", bold=True)
stat_text = (
    "Data will be entered in Microsoft Excel and analyzed using SPSS version 26.0. "
    "Continuous variables will be expressed as mean ± SD or median (IQR). Categorical variables will be "
    "expressed as frequency and percentage. "
    "Comparison of PDL2 and Ki67 expression across three groups (OPMDs, OSCC margins, normal mucosa) will be "
    "performed using one-way ANOVA or Kruskal-Wallis test as appropriate, with post-hoc pairwise comparison. "
    "Correlation between PDL2/Ki67 expression and clinicopathological variables will be assessed by Chi-square "
    "test or Fisher's exact test (categorical) and Spearman's rank correlation (continuous). "
    "Survival analysis (3-year OS and DFS) will be performed using Kaplan-Meier curves and compared with "
    "log-rank test. Independent predictors of survival will be identified by Cox proportional hazard regression. "
    "Interobserver agreement will be evaluated by Cohen's κ coefficient. "
    "A p-value <0.05 will be considered statistically significant."
)
add_body(stat_text)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# REVIEW OF LITERATURE
# ══════════════════════════════════════════════════════════════════════════════
add_heading_style("REVIEW OF LITERATURE", level=2)

reviews = [
    ("Pachpande et al. (2023)",
     "assessed PD-L1 expression by IHC in 40 cases each of OPMDs and OSCC. PD-L1 immunopositivity was "
     "significantly higher in OSCC compared to OPMDs and normal mucosa, with a progressive increase from "
     "benign to premalignant to malignant lesions. The authors concluded that PD-L1 may serve as a "
     "biomarker of malignant transformation and disease aggressiveness in oral lesions.[3]"),

    ("Sonone et al. (2026) [JMIR Research Protocols]",
     "published a protocol for a retrospective cross-sectional study assessing PD-L1 combined positive "
     "score (CPS) expression in OPMDs and OSCC tumor-free surgical margins using the SP263 clone. The study "
     "design included 20 OPMDs, 20 OSCC surgical margin cases, and 20 normal mucosa controls. The study "
     "aimed to correlate PD-L1 expression with 3-year overall survival and disease-free survival. "
     "This protocol serves as an important methodological reference for the present study, which extends "
     "the design to include PDL2 and Ki67 simultaneously.[Published in JMIR Res Protoc 2026;15:e82568]"),

    ("Dave et al. (2020)",
     "reported that PD-1 and PD-L1 expression increased significantly from normal mucosa through OPMDs "
     "to invasive OSCC in a pilot study. These findings support the role of PD-axis molecules in early "
     "oral carcinogenesis and provide a rationale for investigating PDL2 - the second ligand - in this "
     "continuum.[10]"),

    ("Yoshida et al. (2018)",
     "investigated the significance of PD-L1 expression in tongue squamous cell carcinoma and found that "
     "PD-L1 positivity was associated with tumor progression and aggressive behavior, suggesting that "
     "PD-axis ligands may serve as early molecular indicators in oral malignancies.[14]"),

    ("Schneider et al. (2018)",
     "demonstrated that PD-1 and PD-L1 expression in primary HNSCC and corresponding lymph node "
     "metastases had a significant impact on clinical outcomes, reinforcing the prognostic value of the "
     "PD-1/PD-L axis in head and neck cancers.[15]"),

    ("Girolami et al. (2020)",
     "conducted a systematic review and meta-analysis of PD-L1 expression in head and neck squamous "
     "precancerous lesions and reported prevalence of PD-L1 positivity across studies, though with "
     "significant heterogeneity in cutoff values and scoring methods.[12]"),

    ("Tojyo et al. (2019)",
     "reported significant associations between PD-L1 expression and p53 status in oral SCC, suggesting "
     "that PD-L1 upregulation may reflect underlying genomic instability. As Ki67 is also regulated by "
     "genomic stability, concomitant evaluation of Ki67 and PDL2 may uncover important co-expression "
     "patterns.[20]"),

    ("Braakhuis et al. (2010)",
     "highlighted field cancerization in head and neck mucosa and demonstrated that histologically "
     "tumor-free surgical margins harbor occult molecular alterations. Molecular biomarker assessment of "
     "such margins, including immune checkpoint molecules such as PDL2 and proliferation markers such as "
     "Ki67, may identify patients at elevated recurrence risk.[4]"),

    ("Ranka et al. (2020)",
     "performed a systematic review on the role of IHC markers in surgical margins of head and neck "
     "carcinoma patients and specifically highlighted PD-L1 among markers with prognostic relevance, "
     "supporting its evaluation in OSCC tumor-free margins.[6]"),

    ("Srivastava et al. (2025)",
     "evaluated PD-L1 expression and its correlation with clinicopathological parameters in OSCC at a "
     "tertiary care center in India, reporting significant associations with tumor grade, nodal status, "
     "and clinical stage. This study provides relevant Indian data supporting a similar investigation "
     "with PDL2 and Ki67.[17]"),
]

for author, text in reviews:
    p = doc.add_paragraph()
    p.paragraph_format.first_line_indent = Inches(0)
    p.paragraph_format.space_after       = Pt(8)
    r1 = p.add_run(f"{author}: ")
    r1.bold = True; r1.font.name = "Times New Roman"; r1.font.size = Pt(12)
    r2 = p.add_run(text)
    r2.font.name = "Times New Roman"; r2.font.size = Pt(12)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# REFERENCES
# ══════════════════════════════════════════════════════════════════════════════
add_heading_style("REFERENCES", level=2)

refs = [
    "Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249.",
    "Ghapanchi J, Ranjbar Z, Mokhtari MJ, et al. The LncRNA H19 rs217727 polymorphism is associated with oral squamous cell carcinoma susceptibility. Biomed Res Int. 2020;2020:1634252.",
    "Pachpande PS, Mandale MS, Bhavthankar JD, Humbe JG, Zanwar P. Assessment of programmed cell death ligand-1 (PD-L1) expression in oral potentially malignant disorders and oral squamous cell carcinoma – an immunohistochemical study. IP Arch Cytol Histopathol Res. 2023;8(3):180-188.",
    "Braakhuis BJ, Bloemena E, Leemans CR, Brakenhoff RH. Molecular analysis of surgical margins in head and neck cancer: more than a marginal issue. Oral Oncol. 2010;46(7):485-491.",
    "Satgunaseelan L, Gupta R, Madore J, et al. Programmed cell death-ligand 1 expression in oral squamous cell carcinoma is associated with an inflammatory phenotype. Pathology. 2016;48(6):574-580.",
    "Ranka R, Chaudhary M, Sharma P, Gawande M, Hande A, Patil S. Role of immunohistochemical markers in surgical margins of patients with head and neck carcinoma – a systematic review. Int J Curr Res Rev. 2020;12(6):09-17.",
    "Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12(4):252-264.",
    "He X, Xu C. Immune checkpoint signaling and cancer immunotherapy. Cell Res. 2020;30:660-669.",
    "Mildner F, Sopper S, Amann A, et al. Systematic review: soluble immunological biomarkers in advanced non-small-cell lung cancer. Crit Rev Oncol Hematol. 2020;153:102948.",
    "Dave K, Ali A, Magalhaes M. Increased expression of PD-1 and PD-L1 in oral lesions progressing to oral squamous cell carcinoma: a pilot study. Sci Rep. 2020;10(1):9705.",
    "Grosso J, Horak CE, Inzunza D, et al. Association of tumor PD-L1 expression and immune biomarkers with clinical activity in patients with advanced solid tumors treated with nivolumab. J Clin Oncol. 2013;31(15_suppl):3016.",
    "Girolami I, Pantanowitz L, Munari E, et al. Prevalence of PD-L1 expression in head and neck squamous precancerous lesions: a systematic review and meta-analysis. Head Neck. 2020;42(10):3018-3030.",
    "Chow LQM, Haddad R, Gupta S, et al. Antitumor activity of pembrolizumab in biomarker-unselected patients with recurrent and/or metastatic head and neck squamous cell carcinoma: KEYNOTE-012 expansion cohort. J Clin Oncol. 2016;34(32):3838-3845.",
    "Yoshida S, Nagatsuka H, Nakano K, et al. Significance of PD-L1 expression in tongue cancer development. Int J Med Sci. 2018;15(14):1723-1730.",
    "Schneider S, Kadletz L, Wiebringhaus R, et al. PD-1 and PD-L1 expression in HNSCC primary cancer and related lymph node metastasis – impact on clinical outcome. Histopathology. 2018;73(4):573-584.",
    "Udall M, Rizzo M, Kenny J, et al. PD-L1 diagnostic tests: a systematic literature review of scoring algorithms and test-validation metrics. Diagn Pathol. 2018;13(1):12.",
    "Srivastava P, Anand N, Agarwal D, et al. Evaluation of programmed death-ligand 1 (PD-L1) expression and its correlation with clinicopathological parameters in oral squamous cell carcinoma. Cureus. 2025;17(6):e85186.",
    "Sonone A, Hande A, Patil S, Pakhale A, Sharma P. Assessment of programmed cell death ligand-1 expression in oral potentially malignant disorders and tumor-free surgical margins of oral squamous cell carcinoma: protocol for a retrospective cross-sectional study. JMIR Res Protoc. 2026;15:e82568. doi:10.2196/82568.",
    "Girolami I, Marletta S, Fiorentino V, et al. Effect of radio-chemotherapy on PD-L1 immunohistochemical expression in head and neck squamous cell carcinoma. J Pers Med. 2023;13(2):363.",
    "Tojyo I, Shintani Y, Nakanishi T, et al. PD-L1 expression correlated with p53 expression in oral squamous cell carcinoma. Maxillofac Plast Reconstr Surg. 2019;41(1):56.",
    "Ahmadi N, Gao K, Chia N, et al. Association of PD-L1 expression in oral squamous cell carcinoma with smoking, sex, and p53 expression. Oral Surg Oral Med Oral Pathol Oral Radiol. 2019;128(6):631-638.",
    "Tang X, Chen S, Sui Q, et al. Response to nivolumab combining radiotherapy and nimotuzumab in metastatic oral squamous cell carcinoma patient with strong PD-L1 expression: a case report. Ann Transl Med. 2020;8(6):402.",
    "Zhang J, Zhang H, Luo Y. Association between activation of the PD-1/PD-L1 pathway and pain in patients with cancer. Med Sci Monit. 2019;25:1275-1282.",
]

for i, ref in enumerate(refs, 1):
    p = doc.add_paragraph()
    p.paragraph_format.left_indent       = Inches(0.3)
    p.paragraph_format.first_line_indent = Inches(-0.3)
    p.paragraph_format.space_after       = Pt(4)
    r = p.add_run(f"{i}. {ref}")
    r.font.name = "Times New Roman"; r.font.size = Pt(11)

page_break()

# ══════════════════════════════════════════════════════════════════════════════
# WORKING PROFORMA
# ══════════════════════════════════════════════════════════════════════════════
add_centered("WORKING PROFORMA", bold=True, size=14, space_before=6, space_after=12)

# ── Section 1: Patient Identification ────────────────────────────────────────
add_heading_style("1. Patient Identification", level=3)
id_fields = ["UHID / Hospital No.", "Date of Registration", "Name", "Date of Biopsy / Surgery"]
for f in id_fields:
    add_fill_line(f)

# ── Section 2: Demographic Data ──────────────────────────────────────────────
add_heading_style("2. Demographic Data", level=3)
add_fill_line("Age (years)")
add_fill_line("Sex")
for opt in ["Male", "Female", "Other"]:
    add_checkbox_item(opt)

add_fill_line("Occupation")
add_fill_line("Residence")
for opt in ["Rural", "Urban", "Semi-urban"]:
    add_checkbox_item(opt)

# ── Section 3: Risk Habits ────────────────────────────────────────────────────
add_heading_style("3. Risk Habits / Etiological Factors", level=3)
habits = [
    "Tobacco smoking (cigarette / bidi / hookah)",
    "Smokeless tobacco (pan masala / gutkha / khaini / mawa)",
    "Betel quid with tobacco",
    "Betel nut alone",
    "Alcohol consumption",
    "Combined tobacco + alcohol",
    "None",
]
for h in habits:
    add_checkbox_item(h)

add_fill_line("Duration of habit (years)")
add_fill_line("Frequency (times/day or packs/year)")

# ── Section 4: Clinical Presentation ─────────────────────────────────────────
add_heading_style("4. Clinical Presentation", level=3)
complaints = [
    "Painless white patch",
    "Painful white patch",
    "Red patch / speckled patch",
    "Restricted mouth opening",
    "Non-healing ulcer",
    "Swelling / growth",
    "Burning sensation",
    "Difficulty in swallowing / speech",
    "Incidental finding",
]
add_body("Chief complaint:", bold=True)
for c in complaints:
    add_checkbox_item(c)

add_fill_line("Duration of symptoms (months)")
add_fill_line("Site of lesion")
sites = ["Buccal mucosa", "Tongue (anterior 2/3)", "Floor of mouth", "Gingiva / Alveolus",
         "Hard palate", "Soft palate", "Retromolar area", "Lip", "Other: ___________"]
for s in sites:
    add_checkbox_item(s)

add_fill_line("Size of lesion (cm)")
add_fill_line("ECOG Performance Status (0-4)")

# ── Section 5: Clinical Diagnosis ────────────────────────────────────────────
add_heading_style("5. Clinical Diagnosis", level=3)
add_body("Group:", bold=True)
for grp in ["Group A – Oral Potentially Malignant Disorder (OPMD)",
            "Group B – Tumor-free Surgical Margin of OSCC",
            "Group C – Normal Oral Mucosa (Control)"]:
    add_checkbox_item(grp)

add_body("Type of OPMD (if applicable):", bold=True)
opmds = ["Leukoplakia (homogeneous)", "Leukoplakia (non-homogeneous / speckled)", "Erythroplakia",
         "Oral Submucous Fibrosis (OSMF)", "Oral Lichen Planus (OLP)", "Erythroleukoplakia", "Other: ___________"]
for o in opmds:
    add_checkbox_item(o)

# ── Section 6: Preoperative Investigations ───────────────────────────────────
add_heading_style("6. Preoperative Investigations", level=3)
inv_fields = ["Hemoglobin (g/dL)", "Total Leukocyte Count", "Platelet Count",
              "Blood Sugar (fasting/random)", "Serum Creatinine", "Liver Function Tests",
              "HIV Status", "VDRL / HBsAg"]
for f in inv_fields:
    add_fill_line(f)

add_body("Imaging:", bold=True)
for img in ["Orthopantomogram (OPG)", "CT scan (Head & Neck)", "MRI (Head & Neck)", "PET-CT scan", "Chest X-ray"]:
    add_checkbox_item(img)

# ── Section 7: Operative Details (for OSCC cases) ────────────────────────────
add_heading_style("7. Operative Details (for OSCC Surgical Margin Cases)", level=3)
add_body("Type of Surgery:", bold=True)
for surg in ["Wide local excision", "Composite resection / Mandibulectomy", "Hemi-glossectomy",
             "Total glossectomy", "Neck dissection (type: _______)", "Other: ___________"]:
    add_checkbox_item(surg)

add_body("Reconstructive procedure:", bold=True)
for rec in ["Primary closure", "Split-thickness skin graft", "Regional flap", "Free flap", "None"]:
    add_checkbox_item(rec)

add_fill_line("Date of surgery")
add_fill_line("Intraoperative frozen section margin status")

# ── Section 8: Gross Pathology ────────────────────────────────────────────────
add_heading_style("8. Gross Pathological Findings", level=3)
add_body("For OSCC primary tumor:", bold=True)
gp_fields = ["Tumor site", "Tumor dimensions (cm) – L × W × D",
             "Depth of invasion (mm)", "Distance of tumor from nearest surgical margin (mm)",
             "Gross appearance (ulcerative / exophytic / infiltrative / verrucous)"]
for f in gp_fields:
    add_fill_line(f)

add_body("Margins submitted (label each):", bold=True)
margin_labels = ["Anterior", "Posterior", "Superior", "Inferior", "Deep / Bone", "Mucosal"]
for m in margin_labels:
    add_checkbox_item(m)

# ── Section 9: Histopathological Findings ────────────────────────────────────
add_heading_style("9. Histopathological Examination (H&E)", level=3)

add_body("For OPMD (Group A):", bold=True)
add_body("Degree of Epithelial Dysplasia (WHO Classification):", bold=False)
for dys in ["No dysplasia", "Mild dysplasia", "Moderate dysplasia", "Severe dysplasia", "Carcinoma in situ"]:
    add_checkbox_item(dys)

add_body("Architectural alterations present:", bold=False)
arch = ["Irregular epithelial stratification", "Loss of polarity of basal cells",
        "Drop-shaped rete ridges", "Increased number of mitoses", "Abnormal superficial mitoses",
        "Premature keratinization", "Keratin pearls within rete ridges", "Loss of epithelial cell cohesion"]
for a in arch:
    add_checkbox_item(a)

doc.add_paragraph()
add_body("For OSCC surgical margin (Group B):", bold=True)
add_body("Margin histology:", bold=False)
for mh in ["Normal epithelium", "Mild dysplasia", "Moderate dysplasia", "Severe dysplasia / CIS",
           "Reactive changes", "Inflammatory infiltrate"]:
    add_checkbox_item(mh)

doc.add_paragraph()
add_body("Primary OSCC tumor characteristics:", bold=True)
add_body("Histological Grade:", bold=False)
for hg in ["Well differentiated (Grade 1)", "Moderately differentiated (Grade 2)",
           "Poorly differentiated (Grade 3)"]:
    add_checkbox_item(hg)

inv_details = ["Depth of invasion (mm)", "Pattern of invasion (cohesive / non-cohesive)"]
for f in inv_details:
    add_fill_line(f)

add_body("Lymphovascular invasion (LVI):", bold=False)
for opt in ["Present", "Absent"]:
    add_checkbox_item(opt)

add_body("Perineural invasion (PNI):", bold=False)
for opt in ["Present", "Absent"]:
    add_checkbox_item(opt)

add_body("Lymph node status:", bold=False)
for opt in ["Not sampled", "Negative (pN0)", "1-2 nodes positive (pN1)", "≥3 nodes or extranodal extension (pN2/3)"]:
    add_checkbox_item(opt)

add_fill_line("TNM / AJCC Stage (8th edition)")
add_fill_line("Final FIGO / pathological stage")

# ── Section 10: IHC – PDL2 ────────────────────────────────────────────────────
add_heading_style("10. Immunohistochemical Findings – PDL2", level=3)

add_fill_line("Antibody clone used")
add_fill_line("Dilution")
add_fill_line("Date of staining")

add_body("PDL2 Expression (Tumour Cells):", bold=True)
add_body("Intensity of staining:", bold=False)
for intens in ["0 – Negative", "1+ – Weak", "2+ – Moderate", "3+ – Strong"]:
    add_checkbox_item(intens)

add_fill_line("Percentage of positive tumour cells (%)")
add_fill_line("H-score (intensity × % positivity)")
add_fill_line("CPS (PDL2-positive cells / total viable tumour cells × 100)")

add_body("PDL2 Positivity Cutoff:", bold=True)
for cut in ["Negative (CPS <1)", "Low positive (CPS 1–9)", "High positive (CPS ≥10)"]:
    add_checkbox_item(cut)

add_body("PDL2 expression in immune cells (TILs / macrophages):", bold=True)
for opt in ["Absent", "Present (mild)", "Present (moderate)", "Present (dense)"]:
    add_checkbox_item(opt)

add_body("Subcellular localization:", bold=True)
for loc in ["Membranous", "Cytoplasmic", "Both"]:
    add_checkbox_item(loc)

add_fill_line("Observer 1 score")
add_fill_line("Observer 2 score")
add_fill_line("Cohen's κ for interobserver agreement")
add_fill_line("Final consensus PDL2 score")

# ── Section 11: IHC – Ki67 ────────────────────────────────────────────────────
add_heading_style("11. Immunohistochemical Findings – Ki67", level=3)

add_fill_line("Antibody clone used (e.g., MIB-1)")
add_fill_line("Dilution")
add_fill_line("Date of staining")

add_body("Ki67 Labelling Index (Ki67-LI):", bold=True)
add_fill_line("Total cells counted")
add_fill_line("Ki67-positive nuclei (brown nuclear staining)")
add_fill_line("Ki67-LI (%) = positive nuclei / total nuclei × 100")

add_body("Ki67 Proliferative Category:", bold=True)
for cat in ["Low (<20%)", "Intermediate (20–50%)", "High (>50%)"]:
    add_checkbox_item(cat)

add_body("Distribution of Ki67 positivity:", bold=True)
for dist in ["Basal layer predominant", "Suprabasal extension", "Full-thickness",
             "Scattered / focal", "Hot-spot areas"]:
    add_checkbox_item(dist)

add_fill_line("Observer 1 Ki67-LI (%)")
add_fill_line("Observer 2 Ki67-LI (%)")
add_fill_line("Mean Ki67-LI (%) used for analysis")
add_fill_line("Intraclass correlation coefficient (ICC)")

# ── Section 12: Combined PDL2 + Ki67 Summary ─────────────────────────────────
add_heading_style("12. Combined PDL2 and Ki67 Expression Summary", level=3)
tbl2 = doc.add_table(rows=4, cols=4)
tbl2.style = "Table Grid"
headers2 = ["Parameter", "Group A (OPMD)", "Group B (OSCC Margin)", "Group C (Normal Mucosa)"]
for i, h in enumerate(headers2):
    cell = tbl2.rows[0].cells[i]
    cell.text = h
    for para in cell.paragraphs:
        for run in para.runs:
            run.bold = True; run.font.size = Pt(10); run.font.name = "Times New Roman"

row_labels = ["PDL2 H-score (mean ± SD)", "PDL2 CPS", "Ki67-LI (%)"]
for ri, label in enumerate(row_labels, 1):
    tbl2.rows[ri].cells[0].text = label
    for ci in range(1, 4):
        tbl2.rows[ri].cells[ci].text = ""
doc.add_paragraph()

# ── Section 13: Correlation with Clinicopathological Parameters ───────────────
add_heading_style("13. Correlation with Clinicopathological Parameters", level=3)

tbl3 = doc.add_table(rows=13, cols=5)
tbl3.style = "Table Grid"
h3 = ["Parameter", "Category", "PDL2 Score", "Ki67-LI (%)", "p-value"]
for i, h in enumerate(h3):
    cell = tbl3.rows[0].cells[i]
    cell.text = h
    for para in cell.paragraphs:
        for run in para.runs:
            run.bold = True; run.font.size = Pt(10); run.font.name = "Times New Roman"

row_data = [
    ("Age", "≤40 / 41-60 / >60"),
    ("Sex", "Male / Female"),
    ("Tobacco habit", "Yes / No / Type"),
    ("Type of lesion / Group", "A / B / C"),
    ("Degree of dysplasia", "None / Mild / Mod / Severe / CIS"),
    ("Histological grade (OSCC)", "WD / MD / PD"),
    ("Depth of invasion (mm)", "<5 / 5-10 / >10"),
    ("LVI", "Present / Absent"),
    ("PNI", "Present / Absent"),
    ("Nodal status", "N0 / N+ "),
    ("TNM stage", "I-II / III-IV"),
    ("Margin status", "Clear / Close"),
]
for ri, (param, cats) in enumerate(row_data, 1):
    tbl3.rows[ri].cells[0].text = param
    tbl3.rows[ri].cells[1].text = cats
    for ci in [2, 3, 4]:
        tbl3.rows[ri].cells[ci].text = ""
doc.add_paragraph()

# ── Section 14: Survival Data ─────────────────────────────────────────────────
add_heading_style("14. Survival and Follow-up Data (where available)", level=3)

add_body("Adjuvant treatment:", bold=True)
for tx in ["Surgery alone", "Post-operative radiotherapy", "Post-operative chemoradiotherapy",
           "Immunotherapy (checkpoint inhibitor)", "None"]:
    add_checkbox_item(tx)

tbl4 = doc.add_table(rows=6, cols=4)
tbl4.style = "Table Grid"
h4 = ["Follow-up Period", "Date", "Disease Status", "Recurrence Site"]
for i, h in enumerate(h4):
    cell = tbl4.rows[0].cells[i]
    cell.text = h
    for para in cell.paragraphs:
        for run in para.runs:
            run.bold = True; run.font.size = Pt(10); run.font.name = "Times New Roman"
periods = ["3 months", "6 months", "12 months", "24 months", "36 months (3-year endpoint)"]
for ri, period in enumerate(periods, 1):
    tbl4.rows[ri].cells[0].text = period
    for ci in [1, 2, 3]:
        tbl4.rows[ri].cells[ci].text = ""
doc.add_paragraph()

add_body("3-year Overall Survival:", bold=True)
for opt in ["Alive, disease-free", "Alive with disease", "Dead due to disease", "Dead due to other cause"]:
    add_checkbox_item(opt)

add_body("3-year Disease-free Survival:", bold=True)
for opt in ["Recurrence-free", "Local recurrence", "Regional recurrence", "Distant metastasis", "Second primary"]:
    add_checkbox_item(opt)

# ── Section 15: IHC Images ────────────────────────────────────────────────────
add_heading_style("15. Photomicrograph Documentation", level=3)

phot_fields = [
    "H&E section (4× overview)", "H&E section (10× / 40× for dysplasia / histological grade)",
    "PDL2 IHC – 4× overview", "PDL2 IHC – 40× representative field",
    "Ki67 IHC – 4× overview", "Ki67 IHC – 40× hot-spot field",
    "Negative control (PDL2)", "Positive control (PDL2)", "Positive control (Ki67)"
]
for pf in phot_fields:
    p = doc.add_paragraph()
    p.paragraph_format.left_indent = Inches(0.3)
    p.paragraph_format.space_after  = Pt(3)
    r = p.add_run(f"☐  {pf}:  Image ID / File: ___________________________")
    r.font.name = "Times New Roman"; r.font.size = Pt(12)

# ── Section 16: Remarks ───────────────────────────────────────────────────────
add_heading_style("16. Remarks / Additional Observations", level=3)
for _ in range(5):
    add_body("_______________________________________________________________")

# ── Signature Block ───────────────────────────────────────────────────────────
doc.add_paragraph()
doc.add_paragraph()
p = doc.add_paragraph()
p.paragraph_format.space_after = Pt(4)
r = p.add_run("Signature of Resident Investigator: ___________________________     Date: ___________")
r.font.name = "Times New Roman"; r.font.size = Pt(12)

p = doc.add_paragraph()
p.paragraph_format.space_after = Pt(4)
r = p.add_run("Signature of Chief Supervisor: ___________________________     Date: ___________")
r.font.name = "Times New Roman"; r.font.size = Pt(12)

p = doc.add_paragraph()
p.paragraph_format.space_after = Pt(4)
r = p.add_run("Signature of Co-supervisor: ___________________________     Date: ___________")
r.font.name = "Times New Roman"; r.font.size = Pt(12)

# ── Save ──────────────────────────────────────────────────────────────────────
out_path = "/tmp/workspace/pdl2-ki67-proforma/Thesis_Proforma_PDL2_Ki67_OSCC.docx"
doc.save(out_path)
print(f"Saved: {out_path}")