Cristin-resultat-ID: 415086
Sist endret: 21. januar 2015, 15:27
Resultat
Vitenskapelig artikkel
1998

Prognosis of intravesical bacillus Calmette-Guerin therapy for superficial bladder cancer by immunological urinary measurements: statistically weighted syndrome analysis

Bidragsytere:
  • A Jackson
  • A Ivshina
  • O Senko
  • A Kuznetsova
  • A Sundan
  • M ODonell
  • mfl.

Tidsskrift

Journal of Urology
ISSN 0022-5347
e-ISSN 1527-3792
NVI-nivå 2

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 1998
Sider: 1054 - 1063

Importkilder

Bibsys-ID: r99002332

Beskrivelse Beskrivelse

Tittel

Prognosis of intravesical bacillus Calmette-Guerin therapy for superficial bladder cancer by immunological urinary measurements: statistically weighted syndrome analysis

Sammendrag

PURPOSE: The goal of this research was to discover new biological ind icators in urine which could be used for short-term prognosis of loca l Bacillus Calmette-Guerin (BCG) therapy outcome in patients with sup erficial bladder cancer. PATIENTS AND METHODS: We measured and statis tically evaluated soluble immunological molecules in urine from bladd er cancer patients (n = 34) receiving BCG intravesically. Urine was c ollected following each of 6 weekly treatments, processed and assayed . The data base included measurements of interleukin-1 (IL-2, IL-4, I L-6, IL-10, IL-12, soluble intercellular adhesion molecule-1 (sICAM-1 ), tumour necrosis factor-alpha (TNF alpha), soluble CD14 (sCD14), in terferon-gamma (IFN gamma), GM-CSF, volume of urine and its pH. The c linical response was evaluated by urine histology and random quadrant biopsy 3 months after the start of therapy. Patients were divided in to 2 groups, with good and poor therapeutic effect. The initial compl ete response rate was 62% (21/34). The data base was analyzed using t raditional multivariate statistical methods and a pattern recognition method which deals with combinatorial-statistical analysis (statisti cally weighted syndromes (SWS) method) of the gradated features. The SWS method is capable of identifying robust patterns in small "fuzzy" sets with high dimensional objects and some missing values. RESULTS: Only one parameter gave significant differences at p

Bidragsytere

A Jackson

  • Tilknyttet:
    Forfatter

A Ivshina

  • Tilknyttet:
    Forfatter

O Senko

  • Tilknyttet:
    Forfatter

A Kuznetsova

  • Tilknyttet:
    Forfatter

Anders Sundan

Bidragsyterens navn vises på dette resultatet som A Sundan
  • Tilknyttet:
    Forfatter
    ved Institutt for klinisk og molekylær medisin ved Norges teknisk-naturvitenskapelige universitet
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