Challenges in Validation of Novel Diagnostic Tools for Pediatric Pneumonia: When Will We Find “The One”?
Notice bibliographique
Résumé
The age-old question continues to reverberate through our hospital walls during respiratory season: “Should I start antibiotics?” Have we finally found our answer? Successfully distinguishing bacterial from viral pneumonia has challenged pediatric hospitalists for decades. Over the years, we have explored more than 20 biomarkers, including white blood cell count, absolute neutrophil count, C-reactive protein (CRP), erythrocyte sedimentation rate, and procalcitonin, to guide our clinical management.1 Systematic reviews indicate that CRP and procalcitonin alone demonstrate suboptimal sensitivity and specificity,1,2 though they may have some utility in ruling out bacterial pneumonia because of their higher negative predictive value at very low levels.3 As in other areas of hospital pediatrics, combining biomarkers with clinical findings has so far proven to be our best approach to making evidence-based decisions.If no single biomarker is sufficient, what about combining them? In their article, “The Association of the MeMed BV Test with Radiographic Pneumonia in Children,”4 Ramgopal et al investigate a combination of 3 biomarkers—CRP, interferon γ–induced protein 10, and tumor necrosis factor–related apoptosis-inducing ligand—into a consolidated score called the BV score, which ranges from 0 to 100. In a previous study, Papan et al identified a cohort of children (N = 1008) with concerns for pneumonia at 2 emergency departments in Italy and Germany.5 They asked a panel of experienced pediatricians to review the medical records of these patients to determine whether each case had bacterial, viral, or indeterminate pneumonia, or a noninfectious cause. When evaluated against bacterial pneumonia determined via expert-based adjudication, BV scores <35 and >65 showed a sensitivity and specificity of 94%, with higher BV scores being associated with bacterial pneumonia.5In this subsequent study published in this issue of Hospital Pediatrics, Ramgopal et al used a subset of that initial cohort to evaluate the association of the BV score with the presence of radiographic pneumonia rather than with expert consensus.4 Radiographic pneumonia was defined as the presence of an infiltrate on chest radiography with or without atelectasis. The study demonstrates that the highest BV score (90–100) was associated with radiographic pneumonia, with ∼20 times increased odds compared with the lowest BV score (0–10). Additionally, the study finds an association between antibiotic use and BV scores, with higher BV scores correlating with higher rates of antibiotic use. No association was noted between the BV score and other evaluated clinical outcomes, including admission rate, length of stay, ICU admission, or use of supplemental oxygen.When assessing the performance of a diagnostic test, a critical factor to consider is whether it is validated against a clinically meaningful measure.6 In this study, radiographic pneumonia serves as the main validation measure.4 However, numerous prior studies have challenged the utility of chest radiography as a diagnostic tool for bacterial pneumonia. In a multicenter study involving more than 2000 children, the presence of consolidation was a poor predictor of bacterial pneumonia when using identified blood and respiratory pathogens as references.7 Ramgopal et al also acknowledge that infiltrates can be present in pneumonia regardless of its etiology—bacterial or viral4,8—and pediatric clinical guidelines do not recommend using chest radiographs to differentiate between bacterial and viral pneumonia.9,10 Furthermore, chest radiograph results are poor predictors of antibiotic prescribing behaviors because a clinical history suggestive of bacterial pneumonia often takes precedence.11,12 The absence of an adequate gold standard complicates the validation of new biomarkers, including the BV score. This underscores a significant challenge in the field of bacterial pneumonia. With the BV score, we risk adding an additional layer of proxy, where the BV score itself is a proxy for chest radiograph findings, which are already a poor predictor of the clinical outcomes of interest in bacterial pneumonia.Aside from the limitations of the gold standard, this study highlights several constraints of the BV score in predicting radiographic pneumonia. Notably, the relationship between the BV score and the outcome of radiographic pneumonia does not appear to be linear. For the lower 4 quintiles of the BV score, the incidence of radiographic pneumonia fluctuated between 26% and 42%. In contrast, only the highest quintile (BV score 90–100) showed a substantial increase, with radiographic pneumonia present in 60% of cases. Interestingly, even the lowest quintile BV score was associated with a 26% probability of radiographic pneumonia. If the presence of radiographic pneumonia significantly influences the decision-making process for subsequent management, this high probability cannot be overlooked in clinical practice. The secondary outcomes of the study also revealed no consistent patterns in hospitalization, length of stay, or oxygen use across different BV score quintiles. A lower BV score, indicative of a reduced likelihood of radiographic pneumonia, corresponded to greater oxygen use, contradicting current evidence that identifies hypoxia as a strong predictor of radiographic pneumonia.13Importantly, we must acknowledge that establishing a new biomarker involves a lengthy and rigorous process requiring extensive testing and validation.14 Additionally, ensuring its accessibility in clinical practice presents another significant challenge. Given these obstacles, it is crucial for any new biomarker to clearly demonstrate superiority over previously studied and currently used options. Unfortunately, the area under the receiver operator characteristic curve for the BV score (0.87) was not significantly better than CRP alone (0.85) or procalcitonin alone (0.83). Moreover, CRP showed a better linear association with radiographic pneumonia compared with the BV score. This suggests that in clinical practice, we might simply be adding another test to our long list of questionable biomarkers rather than finding a better replacement.Considering these limitations, can we reach any definitive conclusions about the BV score? Not yet, though there is room for further research. A more comprehensive analysis of how this diagnostic test could be integrated into clinical practice is needed. Perhaps the test may have value in reducing the overuse of chest radiography and antibiotics among patients with lower BV scores. Given that this biomarker has only been studied in a single cohort of pediatric patients at risk for bacterial pneumonia, it is premature to generalize these findings. Future research is needed to externally validate the BV score against a clinically meaningful gold standard in a different patient cohort, compare its diagnostic efficacy with commonly used biomarkers such as CRP and procalcitonin, and evaluate its potential effects on clinical outcomes. Consequently, we find ourselves at an impasse for the time being, and it appears that our ears and history-taking skills may still surpass any single diagnostic test available. Unfortunately, we may not have found “the one” quite yet.
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 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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».