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Abstract P5-09-01: Nottingham prognostic index plus (NPI+): Validation of the modern clinical decision making tool in breast cancer

2015· article· en· W2337185978 on OpenAlexaff
Andrew R. Green, Daniel Soria, Jacqueline Stephen, Desmond G. Powe, Christopher C. Nolan, Ian Kunkler, Jeremy Thomas, G.R. Kerr, W Jack, David Camreron, Tammy Piper, Graham Ball, Jonathan M. Garibaldi, Emad A. Rakha, John M.S. Bartlett, Ian O. Ellis

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsNottingham Prognostic IndexMedicineOncologyInternal medicineStage (stratigraphy)Breast cancerAdjuvant therapyCytokeratinPrognostic variableMitotic indexCancerEstrogen receptorGynecologyImmunohistochemistryBiology

Abstract

fetched live from OpenAlex

Abstract Introduction Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. The Nottingham Prognostic Index Plus (NPI+) is based on the assessment of biological class combined with established clinicopathologic prognostic variables providing improved patient outcome stratification superior to the traditional NPI*. This study aimed to validate the NPI+ in an independent series of BC. Methods A Validation series of 469 primary early-stage BC cases treated in Edinburgh, UK were matched for size, stage and grade to cases from Nottingham, UK used to develop the NPI+ (Training series). Adjuvant therapy was similar in both series except that 143 Edinburgh cases received endocrine therapy whilst the matched Nottingham cases had no adjuvant therapy. However, there was no significant difference in 10 year BC specific survival (BCSS) between the Training and Validation series. Cases, prepared as TMAs, were immunohistochemically assessed for Cytokeratin (Ck)5/6, Ck18, EGFR, Estrogen Receptor (ER), Progesterone Receptor (PgR), HER2, HER3, HER4, Mucin 1 and p53 expression. NPI+ biological class based on the expression of the 10 biomarkers was determined. Subsequent NPI+ prognostic scores were assigned using individual algorithms for each biological class developed using the Training series incorporating clinicopathologic parameters: positive nodes (including nodal stage), tumour size, tumour grade (including mitotic index) and PgR. NPI+ biological classes, prognostic scores and prognostic groups were compared between the Validation and Training series and their role in prediction of patient outcome. A p-value of <0.01 was considered significant. Results As anticipated, there was a comparable distribution of NPI+ biological classes between Training and Validation series: Luminal A, n=143 (31%) vs n=115 (25%); Luminal N, n=99 (21%) vs n=89 (19%); Luminal B, n=75 (16%) vs n=85 (18%); Basal p53 altered, n=54 (12%) vs n=72 (15%); Basal p53 normal, n=37 (8%) vs n=53 (11%); HER2+/ER+, n=31 (7%) vs 18 (4%); HER2+/ER-, n=30 (6%) vs n=37 (8%; X2=13.792, p=0.032). BCSS was analogous between the Validation and Training series in each of the NPI+ biological classes except Luminal B (p=0.042). Similar BCSS was observed in the NPI+ Biological classes of the Training versus Validation series when taking into consideration adjuvant treatment modalities. The mean NPI+ score was similar between the Validation and Training series (2.30 vs 1.89, Pearson’s Regression p=0.079). The NPI+ prognostic groups significantly predicted patient outcome in each molecular class (BCSS, p<0.0001) in the Validation series irrespective of adjuvant treatment. Comparing the BCSS in each of the NPI+ prognostic groups demonstrated there were no significant differences between patient outcome in each of the NPI+ prognostic groups between the Validation and Training series. Conclusion This study validates the NPI+ in an independent series of primary BC confirming its’ reproducibility. The NPI+ provides improved individualised clinical decision making for breast cancer for both prediction of clinical outcome and relevant therapeutic options. Acknowledgements Funded by the MRC References *Rakha EA et al Br J Cancer. 2014 110:1688-97. Citation Format: Andrew R Green, Daniel Soria, Jacqueline Stephen, Desmond G Powe, Christopher C Nolan, Ian Kunkler, Jeremy Thomas, Gill Kerr, Wilma Jack, David Camreron, Tammy Piper, Graham R Ball, Jonathan M Garibaldi, Emad A Rakha, John MS Bartlett, Ian O Ellis. Nottingham prognostic index plus (NPI+): Validation of the modern clinical decision making tool in breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P5-09-01.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.107
GPT teacher head0.454
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
Has abstractyes

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