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Record W3009173572 · doi:10.1089/thy.2019.0592

A Prospective Mixed-Methods Study of Decision-Making on Surgery or Active Surveillance for Low-Risk Papillary Thyroid Cancer

2020· article· en· W3009173572 on OpenAlexafffundabout
Anna M. Sawka, Sangeet Ghai, Tom Yoannidis, Lorne Rotstein, Patrick Gullane, Ralph Gilbert, Jesse D. Pasternak, Dale Brown, Antoine Eskander, John R. de Almeida, Jonathan C. Irish, Kevin Higgins, Danny Enepekides, Eric Monteiro, Avik Banerjee, Manish D. Shah, Everton Gooden, Afshan Zahedi, Mark Korman, Shereen Ezzat, Jennifer M. Jones, Valeria E. Rac, George Tomlinson, Aleksandra Stanimirovic, Amiram Gafni, Nancy N. Baxter, David P. Goldstein

Bibliographic record

VenueThyroid · 2020
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsGrand River HospitalTed Rogers Centre for Heart ResearchWilliam Osler Health SystemPrincess Margaret Cancer CentreMount Sinai HospitalNorth York General HospitalSt. Michael's HospitalSunnybrook Health Science CentreWomen's College HospitalHamilton Health SciencesUniversity of TorontoUniversity Health Network
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchLotte and John Hecht Memorial Foundation
KeywordsMedicineInterquartile rangeConfidence intervalProspective cohort studyThyroidectomyInternal medicineSurgeryThyroid

Abstract

fetched live from OpenAlex

Background: Active surveillance (AS) of small, low-risk papillary thyroid cancers (PTCs) is increasingly being considered. There is limited understanding of why individuals with low-risk PTC may choose AS over traditional surgical management. Methods: We present a mixed-methods analysis of a prospective observational real-life decision-making study regarding the choice of thyroidectomy or AS for management of localized, low-risk PTCs <2 cm in maximum diameter (NCT03271892). Patients were provided standardized medical information and were interviewed after making their decision (which dictated disease management). We evaluated patients' levels of decision-self efficacy (confidence in medical decision-making ability) at the time information was presented and their level of decision satisfaction after finalizing their decision (using standardized questionnaires). We asked patients to explain the reason for their choice and qualitatively analyzed the results. Results: We enrolled 74 women and 26 men of mean age 52.4 years, with a mean PTC size of 11.0 mm (interquartile range 9.0, 14.0 mm). Seventy-one patients (71.0% [95% confidence interval 60.9–79.4%]) chose AS over surgery. Ninety-four percent (94/100) of participants independently made their own disease management choice; the rest shared the decision with their physician. Participants had a high baseline level of decision self-efficacy (mean 94.3, standard deviation 9.6 on a 100-point scale). Almost all (98%, 98/100) participants reported high decision satisfaction. Factors reported by patients as influencing their decision included the following: perceived risk of thyroidectomy or the cancer, family considerations, treatment timing in the context of life circumstances, and trust in health care providers. Conclusions: In this Canadian study, ∼7 out of 10 patients with small, low-risk PTC, who were offered the choice of AS or surgery, chose AS. Personal perceptions about cancer or thyroidectomy, contextual factors, family considerations, and trust in health care providers strongly influenced patients' disease management choices.

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)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.371
Teacher spread0.343 · 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 designQualitative
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".

Quick stats

Citations67
Published2020
Admission routes3
Has abstractyes

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