CORR Insights®: The Pediatric Toronto Extremity Salvage Score (pTESS): Validation of a Self-reported Functional Outcomes Tool for Children with Extremity Tumors
Notice bibliographique
Résumé
Where Are We Now? Outcomes following treatment can be determined with the use of disease-specific outcomes tools like the WOMAC for hip and knee osteoarthritis or, if one seeks a more-holistic view of the patient’s overall well-being, then the use of broader functional outcomes and/or health-related quality of life measures may be more appropriate. While subspecialists may tend to focus on disease or even joint-specific scales, the understanding of a patient’s overall outcome is likely to be incomplete if function and health-related quality of life are not measured [1]. Most oncology studies now include function and health-related quality of life measures, and perhaps because of this, some have delivered important findings [3, 5, 7]. For example, one study found that anxiety and depression was the domain with the greatest change between the time of diagnosis of adult soft-tissue sarcoma and 1-year following completion of treatment [3]. Another study found that body image issues and mobility concerns are common among survivors of sarcoma and these individuals may be reluctant to share these concerns with their providers [7]. Finally, a study on Ewing’s sarcoma survivors reported mild-to-moderate disability and impairments in 32% of patients, with older patients, females, and those with a pelvic site of disease to be at greatest risk of long-term issues [5]. These studies exemplify the importance of a more comprehensive outcome measurement compared to disease-specific or functional outcomes alone. Standardization of health-related quality of life tools and interpretation among children, adolescents, and young adult populations has been recommended on the basis of results from a systematic review [6], in order to improve the information provided by these measures. Before including either functional or health-related quality of life outcome measures in a study, the measurement tool must be validated in the specific population in which it is intended to be used. Absent this information, it is not possible to know whether the outcome tool measures what it intends to measure or does so accurately or in a valid way. In the current study, Piscione and colleagues [4] accomplished this critical task for the pediatric population with benign and malignant bone tumors. By developing and subsequently validating a measure of physical function specific to this patient population, they have contributed a means by which to determine patient reported physical function amongst children and adolescents. Where Do We Need To Go? Although it is critical to validate and increase the use of functional outcomes and health-related quality of lives for patients with cancer, more in-depth information is needed to understand how this patient population achieves those outcomes, as well as the best ways to provide treatments to improve function and quality of life. We lack more than we know in these areas. As an example of the incomplete information provided by functional outcome measures, Barrera and colleagues [2] found a similarity in patient-reported health-related quality of life scores between adolescent and young adult survivors of pediatric bone sarcoma treated with either amputation or limb salvage. The authors found that those surveyed did not demonstrate a preference between the two treatments [2], illuminating our incomplete understanding of outcome from the patient perspective. There is an even greater paucity of information regarding potential interventions to improve the modifiable determinants of outcome. In order to not only manage the disease, but also allow patients to feel better, we need to better understand the potential interventions that will address the entire individual. To illustrate this point, one can start with the finding that anxiety and depression symptoms have the greatest change over the course of adult soft-tissue sarcoma treatment [3] and postulate that interventions assisting with the emotional implications of a cancer diagnosis and its treatment could be of benefit to the patient, leading to improvement in health-related quality of life outcome. A systematic review of patients with advanced stages of cancer has demonstrated exactly that, specifically reporting improved quality of life and reduced anxiety and depression through the use of mindfulness meditation practices [9]. Additionally, lack of sleep has been demonstrated to be associated with an increased risk of anxiety and depression [8]. Future studies should determine whether interventions focused on improving sleep among patients with cancer can lead to improved health-related quality of life outcomes. Symptoms of anxiety and depression can be evaluated through the use of health-related quality of life measures, such as the SF-36 or EQ-5D, which have specific domains for determination of such symptoms. How Do We Get There? When treating children with cancer, orthopaedic surgeons must not only treat the disease, but also provide comprehensive supportive care for the patient as well as his or her family. Many potentially beneficial treatments, such as mindfulness meditation, gratitude and optimism training, sleep hygiene, and nutrition are widely used in the general population and there is every reason to hypothesize their benefit in improving quality of life. Prospective studies utilizing validated health-related quality of life measures can fill the gaps in our knowledge that remain, and can help us choose those interventions that yield the greatest improvements in quality of life, which is so important to patients with cancer. The potential for harm from mindfulness meditation training, gratitude and optimism training, sleep hygiene, and nutrition is low and the potential benefit, particularly for health-related quality of life, cannot be overstated. Multicenter prospective studies could be designed using health-related quality of life measures as an outcome to provide evidence regarding the domains with the greatest impact on outcome. Such studies can be developed using existing collaborative networks and available outcome measures. To date, there is a paucity of such studies however this reflects more a lack of interest to date rather than feasibility. Given the favorable risk-benefit profile of interventions like mindfulness meditation, gratitude and optimism training, sleep hygiene, and nutrition, prospective studies can be developed to implement one or a combination of these interventions and study their impacts on health-related quality of life outcome during and following treatment. Although these interventions may seem beyond what is likely to be accepted by children, there are many examples of mindfulness and gratitude training being utilized in schools to reduce conflict and improve concentration. Sleep hygiene and nutrition can be potentially improved through educating parents and caregivers. This paradigm need not only be applied to children as the potential benefit to adults is equally great.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,005 |
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 source (Gemma direct ou Codex distillé), 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 ».