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Abstract P2-14-02: Complications of breast reconstruction in a provincial population of breast cancer survivors

2015· article· en· W981418970 on OpenAlexaffabout
Elaine S. Wai, Ling Lü, Cheryl Alexander, Mary Lesperance, Mary L. McBride, Scott Tyldesley, Chris Taylor

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsUniversity of VictoriaUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineBreast cancerMastectomyBreast reconstructionPopulationCohortCancerSurgeryGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Breast cancer is the most prevalent cancer in women in Canada. There are varying reports of the use of breast reconstruction in various populations and very few prospective trials or population reports of complications related to breast reconstruction in breast cancer patients. The goal of this study is to describe the use of breast reconstruction in breast cancer survivors in British Columbia, the risk of complications after breast reconstruction, and factors associated with a higher risk of complications. Methods: Electronic Records from the BC Cancer Agency were used to identify women diagnosed with invasive breast cancer between 2001-2008 in British Columbia. Administrative hospital records used with permission of the British Columbia Ministry of Health, obtained through PopulationData BC, were used to obtain details about all surgeries,hospital admissions and associated complications for the cohort. Analyses of reconstruction for those treated with breast-conserving surgery (BCS) versus mastectomy were done separately. For those who underwent mastectomy following BCS, complications after BCS before mastectomy were attributed to the BCS, and those that occurred after mastectomy were attributed to the mastectomy. These analyses included a description of the type of reconstruction procedures used in this era, and the frequency and types of complications after the reconstruction procedures. Logistic regression was used to identify risk factors for complications post reconstruction. Results: The cohort consisted of 18,642 women; 4868 had mastectomy alone, 8633 had BCS alone, 2894 had both, and 2247 had neither surgery. Of those undergoing BCS (11527), 746 had reconstructive procedures. Most of these were separate procedures; 55% were ≤50 years of age. The most common complication was "miscellaneous complication of internal prosthetic devices, implants or grafts". One hundred eight (14%) of those with reconstruction after BCS had complications within 30 days of the reconstruction procedure, 134 (18%) had complications within one year of the procedure. Of those undergoing mastectomy (7762), 7497 had their mastectomies within 1 year of diagnosis. Ninety-six had bilateral mastectomies. 1766 underwent reconstructive procedures; 74% were immediate procedures, 57% were ≤ 50 years of age. The most common complication was "miscellaneous complication of internal prosthetic devices, implants or grafts". One hundred sixty-seven (9%) of those with reconstruction after (or with) mastectomy had complications within 30 days of the reconstruction procedure, 227 (13%) had complications within one year of the procedure. Regression analysis showed that no radiotherapy (OR=0.65) and premenopausal status (OR=0.70) were significantly associated with a lower risk of complication post reconstruction. Conclusion: Complications related to reconstructive procedures for breast cancer happened in the minority of breast cancer survivors. They were more common in those with BCS, and were more likely for those who underwent adjuvant radiotherapy or were postmenopausal. Citation Format: Elaine S Wai, Ling Hong Lu, Cheryl Alexander, Mary L Lesperance, Mary L McBride, Scott Tyldesley, Chris Taylor. Complications of breast reconstruction in a provincial population of breast cancer survivors [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 P2-14-02.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.859
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.096
GPT teacher head0.398
Teacher spread0.302 · 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 routes2
Has abstractyes

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