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Trajectory of symptoms reported in remote symptom monitoring over the course of oncology treatment for gynecologic cancers.

2022· article· en· W4298139337 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Behavioral Studies
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Institutes of Health
KeywordsMedicineInterquartile rangeGynecologic oncologyCancerInternal medicineGynecologic cancerStage (stratigraphy)Physical therapyOvarian cancer

Abstract

fetched live from OpenAlex

270 Background: Patients now have the ability to utilize electronic patient reported outcomes (ePROs) for remote symptom monitoring (RSM). This analysis seeks to better understand trajectory of reported symptoms during treatment for patients with gynecologic cancer participating in RSM. Methods: We approached patients with gynecological cancer initiating treatment at the Mitchell Cancer Institute (MCI) between 7/1/21-4/30/2022. Patients were eligible if they were starting chemotherapy, targeted therapy, or immunotherapy for a new cancer. Patients seeking a second opinion were excluded. Enrolled patients received symptom survey (PRO-CTCAE questions) via text or email once per week. Initially, only severe alerts were forwarded to the clinical care team; moderate alerts were forwarded to clinical teams once they were comfortable with alert management. Patients completed symptom assessments for 24 weeks or until withdrawal. Patient age at enrollment, race, sex, cancer type, cancer stage, and PROs were abstracted from electronic health records and the PRO platform (Carevive). Descriptive statistics were calculated using frequencies and percentages for categorical variables and median and interquartile ranges (IQR) for continuous variables. Results: A total of 60 female patients with gynecological cancer were enrolled; 33% were Black or African American and 67% were White; median age was 61 years (IQR 53-68). Seventy-eight percent (47/60) of patients reported 379 symptoms with at least one moderate or severe alert during this time period; 32% considered moderate and 68% considered severe. Overall, the most frequently reported symptom was pain (29%). At baseline (week 0), 14% and 41% of 56 patients reported moderate symptoms and severe symptoms, respectively. Symptom burden decreased over time with 4% and 7% of 27 patients who completed a survey at 12 weeks reporting moderate and severe symptoms. Specific symptom trajectories followed similar patterns. Conclusions: In our sample, patients reported the majority of symptoms during the first three months of treatment. Symptom trajectory decreased with time, suggesting symptoms are being effectively monitored and addressed by the clinical teams engaging in RSM. Future research is needed to understand if symptom improvement translates to increased quality of life, decreased hospitalizations, and increased survival for patients, as well as lessen the burden of call volume on the clinical team.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.295
GPT teacher head0.549
Teacher spread0.253 · 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