ISSN:
1432-1335
Schlagwort(e):
Key words LDH
;
Prognosis
;
Small-cell lung cancer
;
Staging
Quelle:
Springer Online Journal Archives 1860-2000
Thema:
Medizin
Notizen:
Abstract Purpose: At present the standard staging procedure in patients with small-cell lung cancer (SCLC) is extensive, expensive and time-consuming. Furthermore, the predictive and prognostic value of the current staging system is poor. To determine the value of pretreatment clinical and biochemical parameters to predict tumour stage and to assess prognosis, a retrospective study was performed of 121 consecutive patients with newly diagnosed SCLC. Methods: On the basis of routine diagnostic procedures, 51 patients were staged as having limited disease and 70 patients as having extensive disease. During follow-up, data on tumour progression and survival were gathered. These data and the tumour stage were correlated with lactate dehydrogenase (LDH), alkaline phosphatase, liver enzymes, leucocyte count, protein, albumin, calcium, age and gender. Results: Follow-up ranged from 1 week to 96 months, during which 110 patients died. In all patients with LDH levels above 400 U/l (n = 31), metastases were found at the initial stage, whereas all patients initially staged as having limited disease and LDH levels above 240 U/l showed tumour progression. Bone and liver were found to be the most commonly involved sites, whereas the incidence of brain metastases increased during follow-up. In patients initially staged as having limited disease, no differences in survival were found between those showing local recurrence and those developing metastases during follow-up (P = 0.67). Compared to the patients initially staged as having extensive disease, the survival of both groups was significantly better (P 〈 0.001). Significant independent variables of survival were LDH, albumin, initial stage and gender, but LDH was the best overall predictor (P 〈 0.001). Conclusion: These results suggest that pretreatment LDH may be used as an additional staging parameter in SCLC, which can identify prognostic subgroups before treatment.
Materialart:
Digitale Medien
URL:
http://dx.doi.org/10.1007/s004320050157
