Case Studies / Delphi expert consensus on postmenopausal hormonal ther…
Medical Affairs KOL & Expert Engagement Gynaecology

Delphi expert consensus on postmenopausal hormonal therapy sequencing: 65 authors, published in peer-reviewed journal

Challenge
Treatment sequencing in postmenopausal hormonal therapy lacked an international expert consensus — creating inconsistent clinical practice and weakening the evidence base for reimbursement arguments.
Approach
Designed and managed a two-round Delphi consensus process: expert recruitment across multiple countries, structured questionnaire design, statistical analysis of consensus, and full peer-reviewed publication support.
Result
Consensus published in a high-impact gynaecology journal; integrated into 2 national clinical guidelines.
The challenge

Treatment sequencing debates without consensus damage everyone — patients, clinicians, and access

Postmenopausal hormonal therapy offered clinicians multiple sequencing options, with different agents appropriate at different stages of disease and different patient profiles. But the clinical literature had not crystallised into a working consensus — different thought leaders in different countries advocated different approaches, and no international guideline body had formally addressed sequencing.

The absence of consensus had downstream consequences. HCPs in non-specialist settings were uncertain about sequencing decisions. Reimbursement bodies were using the lack of consensus to justify restrictive prescribing conditions. The brand's own medical positioning was complicated by the competing voices of equally credible experts.

A properly conducted, methodologically transparent Delphi process was the only approach that could produce a credible consensus — one that would be taken seriously by guideline bodies and HTA committees.

A Delphi consensus is not a marketing document. It is a scientific methodology with strict requirements for participant independence, question design, and statistical analysis. Done correctly, it produces something no individual expert statement can: a credible collective position.

Our approach

What we did

1
Expert panel recruitment
Identified and approached 80 specialists across multiple countries, balancing geography, institutional representation, and scientific perspectives including both advocates and sceptics of different sequencing approaches. 65 accepted and completed both rounds.
2
Questionnaire design — Round 1
Developed 47 statements covering sequencing criteria, patient selection factors, safety monitoring, and patient preference considerations. Statements drafted with a scientific writing team and reviewed by a methodologist for Delphi appropriateness.
3
Round 1 analysis
Collected responses and calculated consensus levels using pre-specified thresholds (>75% agreement for consensus). 31 statements reached consensus in Round 1; 16 required a second round with revised formulations.
4
Round 2 and final analysis
Sent revised statements with Round 1 results to all participants. Final analysis: 44 of 47 statements reached consensus. 3 remaining statements documented as areas of genuine clinical disagreement.
5
Manuscript preparation and submission
Prepared a full manuscript with methods, results, and clinical implications sections. Managed co-author review across 65 authors. Submitted to a leading gynaecology journal. Addressed two rounds of peer reviewer comments. Publication accepted within 6 months.
Result

Measurable impact

The Delphi consensus paper was published in a high-impact gynaecology journal, with 65 co-authors and 44 consensus statements. Two national gynaecology societies subsequently incorporated the consensus recommendations into their updated clinical guidelines. The paper is now routinely referenced in HTA submissions for the therapeutic class.

65
Co-authors across multiple countries — two-round Delphi
44/47
Statements reaching pre-specified consensus threshold
2
National clinical guidelines incorporating the consensus recommendations
Facing a similar challenge?

Tell us what you’re working on — we’ll show you relevant cases and suggest the fastest path forward.

Evidence Scanner
Evidence ScannerTM
AI infrastructure

AI-powered.
Expert-validated.

We built AI workflows into our daily practice — not as a marketing claim, but as the infrastructure that lets our medical experts deliver faster without cutting corners.

Research
Structured PubMed queries with narrative or table outputs
Monitoring
Weekly literature digests by drug, target, or topic
AI-Enhanced EDC
Electronic data capture with AI-assisted structuring of unstructured records
Fact-Checker
Claim verification against your source documents
AI accelerates. Our experts validate.
Every output goes through expert medical review before it reaches your team. AI handles structure and speed — we handle scientific judgement and MLR readiness.
Evidence Scanner · Research module
// Query: ribociclib OS data MONALEESA 2023–24
search("ribociclib overall survival", {
  years: [2023, 2024],
  output: "structured_table"
})
// 847 records → 23 relevant
Processing 847 records...
Evidence Summary
MONALEESA-2 updated OS (NEJM 2023): median OS 63.9 mo vs 51.4 mo (HR 0.76, 95% CI 0.63–0.93). Benefit maintained across all pre-specified subgroups...