Reply to Hao and He
Bibliographic record
Abstract
To the Editor—We thank Drs Hao and He for their interest in our meta-analysis on the diagnosis of Pneumocystis pneumonia (PcP) by polymerase chain reaction (PCR). We agree that initiation of PcP treatment and underlying conditions likely have an impact on fungal burden and, subsequently, PCR performance. Our meta-analysis found no significant difference in PCR performance according to human immunodeficiency (HIV) status. Unfortunately, it was not possible to perform a stratified analysis according to other underlying conditions, patient demographics, or medication status as the studies included seldom presented sufficient data for comparative analysis according to these factors. We acknowledge inconsistent reporting as a limitation in our discussion, which should ideally be addressed in future studies. The impact of the anti-Pneumocystis therapy, be it prophylaxis, empirical, or targeted therapy, should be considered. The impact of anti-Pneumocystis prophylaxis on PCR performance is understudied, although this may be less relevant given that rates of PcP in patients on sulfamethoxazole-trimethoprim prophylaxis are low (<1%) [1]. Molecular tests have demonstrated the ability to detect resistant/breakthrough infections, indicating that the disease burden is sufficient to be detected by PCR [2]. The effect of empirical treatment on PCR positivity has not been fully investigated, particularly in HIV-negative patients in whom fungal burdens are lower and impact may be greater. Every effort should be made to obtain a respiratory specimen for PCR before starting treatment. Bronchoscopy may be delayed due to the need for specialist equipment and expertise so more readily available specimens, such as induced sputum and upper respiratory tract samples, are useful samples for combining with serum (1,3)-β-d-glucan (BDG). Similarly, the impact of targeted antifungal therapy on PCR performance has not been fully elucidated, although persisting PCR positivity is a poor prognostic marker in PcP and burden typically reduces within 10 days of successful therapy [3, 4]. There is a clear need for further studies evaluating the diagnostic accuracy of standardized PCR methods against the reference standard, with comparative performance according to underlying disease, use of prophylaxis, and timing of treatment initiation. We believe our methods are in line with PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines and additional information is available in the supplementary material. When formatting our search terms, we considered the Population, Intervention, Comparator, Outcome, Study design (PICOS) principle to the extent that it is applicable to noninterventional diagnostic studies. In our systematic review, we did not provide a formal GRADE (Grading of Recommendations Assessment, Development and Evaluation) assessment of the certainty of the evidence because it is primarily designed for systematic reviews on interventional studies. Detailed guidance for rating certainty in comparative diagnostic accuracy reviews is still under development [5]. The studies included were of high methodological quality according to the QUADAS-2 tool, but the certainty of the evidence could only be classified as moderate due to the absence of proven infection, the most typical classification when managing respiratory fungal diseases. There are substantial challenges to achieving global standardization of PcP PCR. Our meta-analysis identified significant variations in PCR methodology across included studies, which will affect the concentration of fungal DNA and diagnostic yield. We also discuss specimen quality and operator skill as a source of heterogeneity that is difficult to quantify. Methodological standardization is being undertaken by the Fungal PCR Initiative (a working group of the International Society of Human and Animal Mycology (ISHAM) and strategies involving external quality-control organizations are being developed to provide an international standard for PcP PCR, potentially allowing it to become the reference test for PcP [6, 7]. We encourage manufacturers to obtain universal approval of their products to enable global availability as the World Health Organization already lists PcP PCR as an essential diagnostic test. Finally, we agree that PCR results should be combined with biomarkers and clinical and radiological findings and our group is exploring diagnostic algorithms that combine all available evidence to enhance diagnosis beyond probable PcP. Financial support. This work was co-funded by the National Institute for Health and Care Research and Manchester Biomedical Research Centre (NIHR203308).
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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 | 0.010 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.019 | 0.031 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".