Challenges in Validation of Novel Diagnostic Tools for Pediatric Pneumonia: When Will We Find “The One”?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".