Accountability

Independent histopathology audit — accession-level analysis

Data source: Pathlab histopathology export (.txt)
Audit unit: Unique pathology accession number (one specimen = one case)
Reporting basis: Independent laboratory data (not self-reported)

Dataset structure

• Total accessions reviewed: 835

• Diagnostic specimens included: 813

• Post-excision clearance specimens: 21

Post-excision clearance specimens were analysed separately and excluded from diagnostic performance metrics.

Classification methodology

• Lesion category assigned solely from the final Diagnosis field

• Clinical indication, narrative, and microscopy text excluded

• Each specimen assigned to a single diagnostic category

• Actinic keratoses (AK) reported separately but excluded from primary benign-to-malignant (B:M) calculations

This approach prevents diagnostic inflation and ensures reproducibility.

Diagnostic yield and case mix

Among 813 diagnostic specimens:

• 384 malignant / pre-malignant lesions

• 429 benign lesions

This corresponds to:

• 47% malignant / pre-malignant

• 53% benign

The workload is therefore cancer-weighted and dominated by non-melanoma skin cancer.

Comparator context

General GP practice typically reports approximately 10–25% malignant lesions.

Mixed-interest skin practice commonly reports 25–35% malignant lesions.

GPwSI and dedicated primary care skin cancer clinics typically report 35–50% malignant lesions.

This audit demonstrated a malignant proportion of 47%.

Benign-to-malignant ratio (AK excluded)

Definitions

Malignant:

• Basal cell carcinoma (BCC)

• Squamous cell carcinoma (SCC, including SCC in situ)

• Melanoma

Benign:

• All remaining diagnoses

Excluded:

• Actinic keratoses

• Post-excision clearance specimens

Result

Benign-to-malignant ratio = 0.95 : 1

Comparator context

General GP practice commonly reports benign-to-malignant ratios of approximately 3–6 : 1.

Mixed-interest skin practice commonly reports 1.5–3 : 1.

GPwSI and dedicated primary care skin cancer clinics commonly report 1–2 : 1.

Published dermatology outpatient series typically report 0.6–1.5 : 1.

This audit therefore sits within the malignant-dominant end of specialist outpatient practice.

Melanoma detection performance

Whole-practice pathology audit

• 33 melanomas diagnosed

• Approximately 25 diagnostic lesions per melanoma detected

This metric reflects overall pathology workload and includes non-melanoma skin cancers, actinic keratoses and benign lesions.

Melanoma-specific audit

An independent PHO audit reviewed lesions excised because melanoma was considered a possible diagnosis.

Melanoma NNT (Number Needed to Treat) = 5.5

This indicates that approximately one melanoma was diagnosed for every 5–6 lesions excised for melanoma exclusion.

Comparator context

A systematic review and meta-analysis of melanoma Number Needed to Treat (NNT) reported the following ranges:

• General practitioners: NNT approximately 9.6–22.6

• Dermatologists: NNT approximately 4.7–9.6

• Pigmented lesion clinics and specialist melanoma services: often <5–10, depending on referral filtering and case selection

Post-excision clearance and margin management

Twenty-one post-excision clearance specimens were identified.

These specimens represent planned margin assessment following a known diagnosis of skin cancer and may include:

• Wider excision following melanoma diagnosis

• Margin-control procedures

• Management of incompletely excised tumours

• Additional clearance where recommended by pathology

They do not represent new diagnostic decisions and were therefore excluded from diagnostic yield calculations and benign-to-malignant ratios.

Overall, approximately 95% of malignant lesions did not require a subsequent clearance specimen.

Comparator context

Published incomplete excision or planned re-excision rates are approximately:

• General practice: 8–30%

• GPwSI skin cancer practice: 2–5%

• Dermatology and plastic surgery series: 2–5%

Observed clearance rates in this audit are consistent with specialist practice.

Methodological strengths

• Accession-based analysis

• Independent pathology source

• Explicit inclusion and exclusion criteria

• Separation of diagnostic and post-treatment specimens

• Reproducible methodology derived from raw Pathlab exports

• Independent PHO verification of melanoma detection performance

Summary

This audit demonstrates a cancer-weighted case mix, malignant-dominant benign-to-malignant ratios, efficient melanoma detection, and structured margin management.

Results are derived from independent pathology data and supported by a separate melanoma-specific PHO audit, providing transparent and reproducible measures of diagnostic performance and treatment outcomes.