RESUMO
Purpose: A diagnostic model to differentiate multiple myeloma (MM) from bone metastasis (BM) in patients with destructive bone lesions (MM-BM DDx) was developed to promote timely and appropriate referral of patients with MM to hematologists. External validation has never been conducted. This study aims to externally validate the performance of the MM-BM DDx model. Patients and Methods: This multi-center external validation study was conducted using retrospective data of patients over 45 years old diagnosed with MM or BM at six university-affiliated hospitals in Thailand from 2016 to 2022. The MM-BM DDx development dataset, including patients from 2012 to 2015, was utilized during external validation. Diagnostic indicators for MM included in the MM-BM DDx model are serum creatinine, serum globulin, and serum alkaline phosphatase (ALP). MM and BM diagnosis was based on the documented International Classification of Diseases 10th Revision codes. Model performance was evaluated in terms of discrimination, calibration, and accuracy. Results: A total of 3018 patients were included in the validation dataset (586 with MM and 2432 with BM). Clinical characteristics were similar between the validation and development datasets. The MM-BM DDx model's predictions showed an AUC of 0.89 (95% CI, 0.87, 0.90). The predicted probabilities of MM from the model increased concordantly with the observed proportion of MM within the validation dataset. The estimated sensitivity, specificity, and LR for each odds class in the validation dataset were similar to those of the development dataset. Conclusion: The discriminative ability and calibration of the MM-BM DDx model were found to be preserved during external validation. These findings provide support for the practical use of the MM-BM DDx model to assist clinicians in identifying patients with destructive bone lesions who are likely to have MM and enable them to arrange timely referrals for further evaluation by hematologists.
RESUMO
The individualized prediction of breast cancer survival (IPBS) model was recently developed. Although the model showed acceptable performance during derivation, its external performance remained unknown. This study aimed to validate the IPBS model using the data of breast cancer patients in Northern Thailand. An external validation study was conducted based on female patients with breast cancer who underwent surgery at Maharaj Nakorn Chiang Mai hospital from 2005 to 2015. Data on IPBS predictors were collected. The endpoints were 5-year overall survival (OS) and disease-free survival (DFS). The model performance was evaluated in terms of discrimination and calibration. Missing data were handled with multiple imputation. Of all 3581 eligible patients, 1868 were included. The 5-year OS and DFS were 85.2% and 81.9%. The IPBS model showed acceptable discrimination: C-statistics 0.706 to 0.728 for OS and 0.675 to 0.689 for DFS at 5 years. However, the IPBS model minimally overestimated both OS and DFS predictions. These overestimations were corrected after model recalibration. In this external validation study, the IPBS model exhibited good discriminative ability. Although it may provide minimal overestimation, recalibrating the model to the local context is a practical solution to improve the model calibration.
RESUMO
INTRODUCTION: Therapeutic recommendations for hidradenitis suppurativa (HS) have recently shifted towards non-invasive pharmacological options. Recent evidence has shown promising efficacy for specific treatments. However, data regarding the comparative efficacy of these treatments in patients with HS are still limited. Therefore, we plan to conduct a systematic review and network meta-analysis (NMA) to summarise the benefits and harms of different pharmacological interventions for treating people living with HS. METHODS AND ANALYSIS: We will search electronic databases, including Medline, Embase, PubMed, Web of Science, Scopus, CINAHL and Cochrane Library beginning from their inception dates with no language restrictions. A grey literature search will be performed to supplement the electronic databases. Both randomised trials and non-randomised studies using validated measurement tools that investigated the benefits and harms of pharmacological interventions among people living with HS will be included. The predefined primary outcomes will include treatment responses that reflect the patient's perspective and all-cause discontinuation. Screening, selection, extraction, assessment of the risk of bias and analysis of the strength of the evidence will be performed independently by a pair of reviewers. A two-step approach of traditional pairwise and NMA will be performed. Based on a random-effects model, standardised weighted mean differences and ORs with corresponding 95% CIs will be pooled as effect estimates for the continuous and categorical endpoints, respectively. Statistical and methodological heterogeneities will be assessed. Preplanned subgroup analyses and univariate meta-regression will be conducted to quantify the potential sources of heterogeneity. Evidence-based synthesis will be based on the magnitudes of effect size, evidence certainty and the surface under the cumulative ranking curve values. ETHICS AND DISSEMINATION: Ethical approval is not required because this study is based on existing published data. These findings will be disseminated through scientific meetings and publications in peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42022302795.
