The aim of the study was to identify variables that may predict the response to neoadjuvant chemotherapy (NACT) in patients with cervical cancer as maturing data from the literature indicate that this therapeutic strategy might be beneficial to some but harmful to others. Clinico-pathologic variables including age, histology, tumor differentiation, as well as immunohistochemical overexpression of p53, mdm2, c-erbB-2, and cathepsin D in 37 of these patients were evaluated as possible predictors of response to the NACT. Fifty-five patients with stage IIB cervical cancer submitted to two courses of cisplatin/ifosfamide/mesna prior to definitive treatment with radical surgery or radiation therapy were the subjects of this study. The clinical response rate was 80% but none of the variables was able to predict response to NACT. Unless methods are found enabling us to predict response and therefore to identify those patients that could benefit from including NACT in the treatment of locally advanced cervical cancer, only women with primarily resectable tumors should be selected for this multimodality approach as a result of the possibility of cross-resistance with radiation therapy in nonresponders.
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http://dx.doi.org/10.1046/j.1525-1438.2000.00022.x | DOI Listing |
BMC Med Imaging
January 2025
Department of Radiological Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Background: Quantitative molecular imaging via single-photon emission computed tomography-derived standardised uptake value (SPECT/CT-SUV) is used to assess the response of metastatic castration-resistant prostate cancer (mCRPC) patients to targeted radionuclide therapy (TRT) with [Lu]Lu-PSMA. This imaging technique determines the radiopharmaceutical distribution and internal dosimetry in patients who receive TRT. However, there is limited evidence regarding the role of image quantification in monitoring changes induced by [Lu]Lu-PSMA.
View Article and Find Full Text PDFBMC Pulm Med
January 2025
State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, China.
Background: Studies on consistency among spirometry, impulse oscillometry (IOS), and histology for detecting small airway dysfunction (SAD) remain scarce. Considering invasiveness of lung histopathology, we aimed to compare spirometry and IOS with chest computed tomography (CT) for SAD detection, and evaluate clinical characteristics of subjects with SAD assessed by these three techniques.
Methods: We collected baseline data from the Early COPD (ECOPD) study.
Background: The proportion of people living with HIV (PLHIV) in Guangxi who are men who have sex with men (MSM) increased rapidly to nearly 10% in 2023; notably, over 95% of this particular population is currently receiving antiretroviral therapy (ART). This study aimed to describe the survival of MSM PLHIV, depict the characteristics and trends of changes in CD4 T cell counts, CD4/CD8 T cell ratio, and viral load, and explore immunological indicators that may be related to mortality during different stages of treatment.
Methods: Immunological indicators of MSM PLHIV receiving ART were extracted and categorized into baseline, mid-treatment, and last values.
BMC Ecol Evol
January 2025
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
Background: In infected hosts, immune responses trigger a systemic energy reallocation away from energy storage and growth, to fuel a costly defense program. The exact energy costs of immune defense are however unknown in general. Life history theory predicts that such costs underpin trade-offs between host disease resistance and other fitness related traits, yet this has been seldom assessed.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Existing prognostic models are useful for estimating the prognosis of lung adenocarcinoma patients, but there remains room for improvement. In the current study, we developed a deep learning model based on histopathological images to predict the recurrence risk of lung adenocarcinoma patients. The efficiency of the model was then evaluated in independent multicenter cohorts.
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