Search PubMed⌕ Search

PubMed · 15485978

Classifying kidney problems: can we avoid framing risks as diseases?

Abstract

The source did not provide an abstract. Follow the original record for more information.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Catherine M Clase, Amit X Garg, Bryce A Kiberd. 2004-10-16. Classifying kidney problems: can we avoid framing risks as diseases?. https://doi.org/10.1136/bmj.329.7471.912

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Diversity in neuroblastomas and discrimination of the risk to progress.

The clinical diversity of Neuroblastomas (NBs) was discriminated into three groups with high sensitivity and specificity to patient's outcome. The 'high risk' NB is defined with any of following conditions, MYCN amplification or unfavorable histology of International Neuroblastoma Pathological Classification (INPC) or low Ha-ras/trk A expression. The 'low risk' NB is defined with all following conditions, single copy of MYCN and INPC favorable histology and high Ha-ras/trk A expression and localized tumor. The remaining NBs were classified into 'intermediate risk' ones. According to these criteria, the diversity of the 248 mass-screening NBs was shown with variety progressive risk; 40% were classified in low risk group, 25% were in high risk group and 35% were in intermediate risk group.

Disease Progression↗

Serum proteomic fingerprinting discriminates between clinical stages and predicts disease progression in melanoma patients.

PURPOSE: Currently known serum biomarkers do not predict clinical outcome in melanoma. S100-beta is widely established as a reliable prognostic indicator in patients with advanced metastatic disease but is of limited predictive value in tumor-free patients. This study was aimed to determine whether molecular profiling of the serum proteome could discriminate between early- and late-stage melanoma and predict disease progression. PATIENTS AND METHODS: Two hundred five serum samples from 101 early-stage (American Joint Committee on Cancer [AJCC] stage I) and 104 advanced stage (AJCC stage IV) melanoma patients were analyzed by matrix-assisted laser desorption/ionisation (MALDI) time-of-flight (ToF; MALDI-ToF) mass spectrometry utilizing protein chip technology and artificial neural networks (ANN). Serum samples from 55 additional patients after complete dissection of regional lymph node metastases (AJCC stage III), with 28 of 55 patients relapsing within the first year of follow-up, were analyzed in an attempt to predict disease recurrence. Serum S100-beta was measured using a sandwich immunoluminometric assay. RESULTS: Analysis of 205 stage I/IV serum samples, utilizing a training set of 94 of 205 and a test set of 15 of 205 samples for 32 different ANN models, revealed correct stage assignment in 84 (88%) of 96 of a blind set of 96 of 205 serum samples. Forty-four (80%) of 55 stage III serum samples could be correctly assigned as progressors or nonprogressors using random sample cross-validation statistical methodologies. Twenty-three (82%) of 28 stage III progressors were correctly identified by MALDI-ToF combined with ANN, whereas only six (21%) of 28 could be detected by S100-beta. CONCLUSION: Validation of these findings may enable proteomic profiling to become a valuable tool for identifying high-risk melanoma patients eligible for adjuvant therapeutic interventions.

Disease Progression↗

Neuroserpin (PI-12) is upregulated in high-grade prostate cancer and is associated with survival.

We carried out Genechip analysis using prostate cancer and non-malignant tissue to identify specific genes related to prostate cancer. We focused on neuroserpin (PI-12), which has been identified as one of the genes with high expression in prostate cancer. We analyzed the relationship between its expression pattern and clinical characteristics. Prostate cancer and normal prostate tissue were analyzed by Affymetrix GeneChip technology. We carried out real-time quantitative PCR on a total of 102 specimens: 45 of normal prostate, 45 of previously untreated prostate cancer (constituting 45 pairs of samples obtained at radical prostatectomy, with each pair dissected from the same prostate specimen) and 12 of recurrent hormone refractory prostate cancer (HRPC). Results showed that the neuroserpin gene was more highly expressed in prostate cancer than in normal prostate tissue. Neuroserpin expression in untreated prostate cancer was significantly higher than that in normal prostate. In HRPC it was significantly higher than that in untreated prostate cancer and normal prostate. In untreated prostate cancer, neuroserpin expression was significantly higher in high grade tumors such as poorly differentiated adenocarcinoma than in lower grade tumors such as well or moderately differentiated adenocarcinoma. Higher neuroserpin expression was associated with shorter recurrence-free survival after radical prostatectomy, shorter recurrence-free survival in HRPC patients and shorter overall survival in HRPC patients. The neuroserpin gene may be associated with the development, progression and aggressiveness of prostate cancer. Our present data suggests that higher neuroserpin expression may predict an unfavorable outcome after radical prostatectomy or hormone therapy.

Disease Progression↗