CORR Insights®: The Pediatric Toronto Extremity Salvage Score (pTESS): Validation of a Self-reported Functional Outcomes Tool for Children with Extremity Tumors
Bibliographic record
Abstract
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.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.012 | 0.005 |
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".