Diagnostic accuracy of the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio in rheumatoid arthritis: a systematic review and meta-analysis.

Existing challenges with the early diagnosis of rheumatoid arthritis (RA) and active disease, mainly by non-rheumatologists, have prompted the search for novel biomarkers. Elevations in indices derived from blood cell counts, e.g., the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), have been reported in RA patients. However, their diagnostic accuracy has not been comprehensively assessed. Therefore, we conducted a systematic review and meta-analysis of studies reporting the sensitivity and specificity of the NLR and PLR, obtained by receiver operating characteristic (ROC) curve analysis, for the presence of RA and active disease. We searched electronic databases from inception to 15 March 2024 and assessed the risk of bias using the JBI Critical Appraisal Checklist (PROSPERO registration number: CRD42024533546). In 15 studies, the NLR exhibited acceptable accuracy for the presence of RA (area under the curve, AUC = 0.76, 95% CI 0.72 to 0.80) and active disease (AUC = 0.70, 95% CI 0.66 to 0.74). The PLR exhibited good accuracy for the presence of RA (AUC = 0.80, 95% CI 0.76 to 0.83). There were insufficient studies to assess the accuracy of the PLR for the presence of active disease. Our systematic review and meta-analysis suggests that the NLR and the PLR are promising biomarkers of RA (NLR and PLR) and active disease (NLR). Further research is required to investigate whether the NLR and PLR can significantly enhance the capacity to diagnose RA and active disease in clinical practice.

Mangoni AA ，Zinellu A 《-》

A systematic review and meta-analysis of the diagnostic accuracy of the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio in systemic lupus erythematosus.

The wide range of clinical and serological manifestations in systemic lupus erythematosus (SLE) and the lack of accepted diagnostic criteria warrant the identification of novel, more accurate biomarkers. Hematological indices derived from full blood cell counts, particularly the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), have shown promise in SLE; however, a critical appraisal of their diagnostic accuracy is lacking. We sought to address this issue by conducting a systematic review and meta-analysis of the diagnostic accuracy of the NLR and PLR in SLE. The electronic databases PubMed, Scopus, and Web of Science were systematically searched from inception to 15 March 2024 for studies reporting the sensitivity and specificity of the NLR and PLR, obtained by receiver operating characteristic (ROC) curve analysis, for the presence of SLE, disease severity, organ involvement (lupus nephritis, pericarditis, and pleural disease), and complications (infections). The risk of bias was assessed using the JBI Critical Appraisal Checklist (PROSPERO registration number: CRD42024531446). The NLR exhibited good accuracy for the diagnosis of SLE (eight studies; area under the curve, AUC = 0.81, 95% CI 0.78-0.85) and lupus nephritis (nine studies; AUC = 0.81, 95% CI 0.77-0.84), but not for severe disease (nine studies; AUC = 0.69, 95% CI 0.65-0.73) or infections (six studies; AUC = 0.73, 95% CI 0.69-0.77). The PLR exhibited good accuracy for the diagnosis of severe disease (six studies; AUC = 0.85, 95% CI 0.81-0.87). There were an insufficient number of studies to assess the accuracy of the PLR for the diagnosis of SLE, lupus nephritis, or infections. No study investigated the NLR and PLR in SLE patients with pericarditis or pleural disease. Therefore, the NLR and the PLR have a relatively high diagnostic accuracy for the presence of SLE and lupus nephritis (NLR) and severe disease (PLR). Further studies are warranted to determine whether the NLR and PLR, in combination with clinical evaluation and other serological biomarkers, can enhance the diagnosis and management of SLE.

Zinellu A ，Paliogiannis P ，Mangoni AA 《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Genedrive kit for detecting single nucleotide polymorphism m.1555A>G in neonates and their mothers: a systematic review and cost-effectiveness analysis.

Shabaninejad H ，Kenny RP ，Robinson T ，Stoniute A ，O'Keefe H ，Still M ，Thornton C ，Pearson F ，Beyer F ，Meader N ... -  《-》

Medications for chronic obstructive pulmonary disease: a historical non-interventional cohort study with validation against RCT results.

Wing K ，Williamson E ，Carpenter JR ，Wise L ，Schneeweiss S ，Smeeth L ，Quint JK ，Douglas I ... -  《-》