Abstract PD12-01: Evaluation of sleep problems and their association with febrile neutropenia, leucopenia and infections in women receiving adjuvant chemotherapy for breast cancer in the Canadian Cancer Trials Group MA.21 trial
Notice bibliographique
Résumé
Abstract BackgroundInsomnia is a frequent complaint in patients with cancer. Sleep problems can affect immune functioning in healthy individuals. Our aim was to evaluate the association between sleep disturbance and the risk of febrile neutropenia, leukopenia and infections in patients treated with chemotherapy in an adjuvant setting for breast cancer.MethodologyThis is a retrospective study using the Canadian Cancer Trial Group data collected for the MA.21 trial, in which three adjuvant chemotherapy regimens (CEF, EC-T dose dense or AC-T) were compared in 2104 patients with node positive or high-risk node negative breast cancer. A total of 1731 patients had completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30) and 1727 patients had completed the Breast Cancer Chemotherapy Questionnaire (BCQ) quality of life questionnaires, which both include a question about sleep difficulties. The primary definition for patients with insomnia was a score of three (quite a bit) or greater at Question 11 (Have you had trouble sleeping? with answers ranging from one (not at all) to four (very much)) on the EORTC QLQ-C30 questionnaire. We compared patients classified as having “clinical insomnia” based on their response to this question with patients considered “good sleepers”. The primary endpoint was the risk of febrile neutropenia. Secondary endpoints were the risks of grade one or more leukopenia, neutropenia and infection. ResultsFebrile neutropenia was more frequent in patients with sleep problems compared with those without, with 16.3% and 12.2% of patients having at least one episode in each group respectively (p value = 0.01 in the univariate analysis (table 1)). However, after adjustment for potential confounders in the multi-variate analysis, it was not statistically significant with an odds ratio of 1.07, a 95% confidence interval of 0.76-1.50 and a p value of 0.71. Similarly, no statistically significant difference in the risk of leukopenia could be demonstrated in the multi-variate analysis for patients with sleep problems with an odds ratio of 0.92 a 95% confidence interval of 0.69-1.24 and a p value of 0.59. No significant association could be found between sleep problems and neutropenia and infections. In an unplanned exploratory analysis, chemotherapy dose reductions were significantly more frequent in patients with sleep problems with 30.6% in this group compared to 21.8% in good sleepers, with a p value <0.0001. ConclusionWhile our univariate analysis suggested an increased risk of febrile neutropenia and leucopenia in patients with sleep problems, after adjustment for confounders, we could not show a statistically significant association in women undergoing adjuvant chemotherapy for high-risk locoregional breast cancer. Table 1: Univariate analysis of primary and secondary outcomes in patients with sleep problems and good sleepersCharacteristicsSleep problem= yesSleep problem = noFebrile neutropeniaNo781 (83.7%)701 (87.8%)Yes152 (16.3%)97 (12.2%)P-value0.01White blood cell count (WBC)Grade 0157 (16.8%)141 (17.7%)Grade 1135 (14.5%)138 (17.3%)Grade 2184 (19.7%)186 (23.3%)Grade 3214 (22.9%)173 (21.7%)Grade 4243 (26.1%)160 (20.1%)P-value0.02NeutropeniaGrade 0778 (83.4%)700 (87.7%)Grade 10 (0%)1 (0.1%)Grade 22 (0.2%)0 (0%)Grade 3152 (16.3%)96 (12.0%)Grade 41 (0.1%)1 (0.1%)P-value0.014InfectionGrade 0619 (66.4%)564 (70.7%)Grade 168 (7.3%)62 (7.8%)Grade 2158 (16.9%)110 (13.8%)Grade 387 (9.3%)61 (7.6%)Grade 41 (0.1%)1 (0.1%)P-value0.24Chemotherapy delayNo1 (0.1%)12 (1.5%)Yes932 (99.9%)786 (98.5%)P-value0.0008Chemotherapy dose reductionNo648 (69.4%)624 (78.2%)Yes285 (30.6%)174 (21.8%)P-value< 0.0001 Citation Format: Audreylie Lemelin, Josée Savard, Michelle Chen, Margot Burnell, Mark N Levine, Lois Shepherd, Bingshu E Chen, Julie Lemieux. Evaluation of sleep problems and their association with febrile neutropenia, leucopenia and infections in women receiving adjuvant chemotherapy for breast cancer in the Canadian Cancer Trials Group MA.21 trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD12-01.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».