Surveillance of Symptom Burden Using the Patient-Reported Outcome Version of the Common Terminology Criteria for Adverse Events in Patients With Various Types of Cancers During Chemoradiation Therapy: Real-World Study
Bibliographic record
Abstract
BACKGROUND: Over 90% of patients with cancer experience 1 or more symptoms caused directly by cancer or its treatment. These symptoms negatively impact on the completion of planned treatment as well as patients' health-related quality of life (HRQoL). It often results in serious complications and even life-threatening outcomes. Thus, it has been recommended that surveillance of symptom burden should be performed and managed during cancer treatment. However, differences in symptom profiles in various patients with cancer have not been fully elucidated for use in performing surveillance in the real world. OBJECTIVE: This study aims to evaluate the burden of symptoms in patients with various types of cancers during chemotherapy or radiation therapy using the PRO-CTCAE (Patient-Reported Outcome Version of the Common Terminology Criteria for Adverse Events) and its impact on quality of life. METHODS: We performed a cross-sectional study of patients undergoing outpatient-based chemotherapy, radiation therapy, or both at the National Cancer Center at Goyang or at the Samsung Medical Center in Seoul, Korea between December 2017 and January 2018. To evaluate cancer-specific symptom burden, we developed 10 subsets for using the PRO-CTCAE-Korean. To measure HRQoL, we used the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Participants answered questions prior to their clinic appointments on tablets. Multivariable linear regression was used to analyze symptoms based on cancer type and to evaluate the association between the PRO-CTCAE items and the EORTC QLQ-C30 summary score. RESULTS: The mean age (SD) of the patients was 55.0 (11.9) years, and 39.94% (540/1352) were male. Overall, symptoms in the gastrointestinal category were the most dominant in all cancers. Fatigue (1034/1352, 76.48%), decreased appetite (884/1352, 65.38%), and numbness and tingling (778/1352, 57.54%) were the most frequently reported. Patients reported more local symptoms caused by a specific cancer. In terms of nonsite-specific symptoms, patients commonly reported concentration (587/1352, 43.42%), anxiety (647/1352, 47.86%), and general pain (605/1352, 44.75%). More than 50% of patients with colorectal (69/127, 54.3%), gynecologic (63/112, 56.3%), breast (252/411, 61.3%), and lung cancers (121/234, 51.7%) experienced decreased libido, whereas 67/112 (59.8%) patients with gynecologic cancer and lymphoma/myeloma reported pain during sexual intercourse. Patients with breast, gastric, and liver cancers were more likely to have the hand-foot syndrome. Worsening PRO-CTCAE scores were associated with poor HRQoL (eg, fatigue: coefficient -8.15; 95% CI -9.32 to -6.97), difficulty in achieving and maintaining erection (coefficient -8.07; 95% CI -14.52 to -1.61), poor concentration (coefficient -7.54; 95% CI -9.06 to -6.01), and dizziness (coefficient -7.24; 95% CI -8.92 to -5.55). CONCLUSIONS: The frequency and severity of symptoms differed by cancer types. Higher symptom burden was associated with poor HRQoL, which suggests the importance of appropriate surveillance of PRO symptoms during cancer treatment. Considering patients had comprehensive symptoms, it is necessary to include a holistic approach in the symptom monitoring and management strategies based on comprehensive patient-reported outcome measurements.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".