PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “prognostic factor”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9Linked to original sources

[Efficiency of lymphocyte immunization by the partner in prevention of unexplained recurrent spontaneous abortion. II. Immunologic prognostic factors].

The prognostic value of some immunological parameters on the course of subsequent pregnancy in 117 women with recurrent spontaneous abortion of unknown etiology subjected to paternal lymphocytes immunization, were estimated. We conclude that neither antinuclear (ANA) nor low titers of anticardiolipin antibodies (ACA), nor mixed lymphocyte reaction--blocking antibodies (MLR-BAbs) have any significant influence on alloimmunization efficiency. However medium or high ACA titers significantly diminish changes for successful alloimmunization and are connected with most complications of subsequent pregnancy.

Abortion, Habitual↗

[Adenocarcinomas of the ethmoid sinus: retrospective analysis of prognostic factors].

OBJECTIVES: Determinate the different prognostic factors of survival in ethmoidal sinus adenocarcinomas (ADK). MATERIAL AND METHODS: 60 patients with ethmoidal sinus ADK. 59 men and one woman. Average of 62.2 years (41-82). Retrospective study between 1985 and 2005. The following data were analyzed: exposure time to wood dust, disease incidence, primary clinical symptoms and ASA score. Radiological data were recovered by tomodensitometry and magnetic resonance imaging. Histological groups were described. TNM classification according to UICC 2002 and Roux/Brasnu was established on clinical and radiological constatations. Different treatments used were analyzed. Estimate of survival rate and impact of different prognostic factors were based on Kaplan-Meier actuarial method and multivariate analysis. RESULTS: Incidence rate was 2.86 patients a year. Exposure average time to wood dust was 25.6 years (2-44). T3/T4 stages were predominant (66.7%). the survival rate was 46.5% at 5 years. The survival rate was significantly superior respectively in T1 and T2 stages than in T3 and T4 stages, and in T4a than in T4b stages. Extension of the lesion to the sphenoid sinus was revealed as a significant bad prognostic factor. The ASA score and the exposure time to wood dust were not identified as statistically significant prognosis factors. CONCLUSION: Survival factors of ethmoïd sinus ADK were T stage and the extension of the tumor to the sphenoid sinus. On the results of this study, we consider that extension in sphenoïd sinus could be include in TNM classification of ethmoïd sinus adenocarcinomas.

Adenocarcinoma↗

Probability imputation revisited for prognostic factor studies.

The analysis of prognostic factor studies by Cox or logistic regression models is often impeded by missing covariate values. In 1990 Schemper and Smith recommended a conditional probability imputation technique (PIT) for the analysis of treatment studies which can be easily applied using standard software and which has been demonstrated to outperform the complete case and omission of covariates strategies. Recent research, however, showed that PIT cannot universally be recommended and it was concluded that model-based methods should be preferred. We agree with these conclusions but also think that there is enough empirical evidence to judge the performance of PIT to be satisfactory in typical prognostic factor studies. Furthermore, comparisons of PIT with multiple imputation in the same context did not indicate an advantage of the latter more involved technique. By means of an analysis of a prostate cancer data set various aspects of application of PIT are discussed, in particular that PIT permits direct comparability of marginal and partial effects analyses. We conclude that PIT continues to be an appropriate and attractive choice for analyses of prognostic factor studies.

Data Interpretation, Statistical↗

Prognostic factors in acquired immunodeficiency syndrome.

To identify prognostic factors in acquired immunodeficiency syndrome (AIDS), the authors studied an inception cohort of 45 patients in a non-endemic area (Group I). The probability of survival was 67% six months after the diagnosis of AIDS and 32% at 12 months. As shown by multivariate Cox regression analysis, survivals were shorter (p less than 0.01) in patients 35 years old or older and in those who had anemia when AIDS was diagnosed. In patients with neither of these poor prognostic factors, the 12-month survival was 64%; in patients with one factor, it was 22%; and in patients with both factors, 0%. The prognostic significance of these two factors was validated in a second inception cohort of 50 patients (Group II): in patients with zero, one, and two poor prognostic factors, the 12-month survivals were 80%, 58%, and 26%, respectively. Other poor prognostic factors in Group I included disseminated Mycobacterium avium-intracellulare and the development of new opportunistic infections or neoplasms. The authors conclude that clinically important prognostic factors can be identified in AIDS patients. These findings should be considered in planning therapeutic trials and in counseling patients.

Acquired Immunodeficiency Syndrome↗

Whole brain radiation therapy in management of brain metastasis: results and prognostic factors.

PURPOSE: To evaluate the prognostic factors associated with overall survival in patients with brain metastasis treated with whole brain radiotherapy (WBRT) and estimate the potential improvement in survival for patients with brain metastases, stratified by the Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA) class. PATIENTS AND METHODS: From January 1996 to December 2000, 270 medical records of patients with diagnosis of brain metastasis, who received WBRT in the Hospital do Cancer Sao Paulo A.C. Camargo in the period, were analyzed. The surgery followed by WBRT was used in 15% of patients and 85% of others patients were submitted at WBRT alone; in this cohort 134 patients (50%) received the fractionation schedule of 30 Gy in 10 fractions. The most common primary tumor type was breast (33%) followed by lung (29%), and solitary brain metastasis was present in 38.1% of patients. The prognostic factors evaluated for overall survival were: gender, age, Karnofsky Performance Status (KPS), number of lesions, localization of lesions, primary tumor site, surgery, chemotherapy, absence extracranial disease, RPA class and radiation doses and fractionation. RESULTS: The OS in 1, 2 and 3 years was 25.1%, 10.4% and 4.3% respectively, and the median survival time was 4.6 months. The median survival time in months according to RPA class after WBRT was: 6.2 class I, 4.2 class II and 3.0 class III (p < 0.0001). In univariate analysis, the significant prognostic factors associated with better survival were: KPS higher than 70 (p < 0.0001), neurosurgery (p < 0.0001) and solitary brain metastasis (p = 0.009). In multivariate analysis, KPS higher than 70 (p < 0.001) and neurosurgery (p = 0.001) maintained positively associated with the survival. CONCLUSION: In this series, the patients with higher perform status, RPA class I, and treated with surgery followed by whole brain radiotherapy had better survival. This data suggest that patients with cancer and a single metastasis to the brain may be treated effectively with surgical resection plus radiotherapy. The different radiotherapy doses and fractionation schedules did not altered survival.

Adult↗

Risk group stratification and prognostic factors in papillary carcinoma of thyroid.

BACKGROUND: Our understanding of the natural history of differentiated thyroid carcinoma has improved with the definition of prognostic factors. These prognostic factors have helped us identify patients in various risk groups. METHODS: A retrospective review of a consecutive series of 810 previously untreated patients with papillary carcinoma of the thyroid was undertaken to analyze the prognostic factors and risk groups. There were 403 patients in the low-risk group, 313 in the intermediate group, and 94 classified in the high-risk group. RESULTS: With a median follow-up of 20 years, 99% survival was achieved in the low-risk group, whereas only 43% survived in the high-risk group. The intermediate-risk group had a 20-year survival of 83%. The favorable prognostic factors included female sex, young age, absence of distant metastases and extrathyroidal extension of the disease, size < 4 cm, and low-grade histology. Focality, presence of lymph node metastasis, and pure papillary or mixed variant had no statistical significance on prognosis. CONCLUSIONS: Based on various prognostic factors, low-, intermediate-, and high-risk groups are identified. Patients in the low-risk group have excellent survival (99%). Appropriate selection of surgical and adjuvant treatment should therefore be used based on prognostic factors and risk group stratification.

Age Factors↗

Thymidine phosphorylase levels as a prognostic factor in renal cell carcinoma.

OBJECTIVE: To investigate the relationship between thymidine phosphorylase (TP), a vascular growth factor, and established prognostic factors for renal cell carcinoma (RCC), e.g. histological grade or Tumour-Node-Metastasis (TNM) classification. PATIENTS AND METHODS: TP levels were measured in RCC tissue (tumour TP) and in adjacent non-neoplastic kidney tissue (normal tissue TP), using a sandwich-type enzyme-linked immunosorbent assay. The 59 patients, diagnosed with organ-confined RCC before surgery and who had undergone radical nephrectomy, were divided into two groups according to their prognosis after surgery. Group 1 (nine patients) had a poor prognosis and group 2 (50) had no evidence of disease within a 65-month follow-up. The relationships among TP level, TNM classification, histological subtypes, V factor and prognosis, and of tumour TP to normal tissue TP levels were investigated. Multiple regression analysis was used to determine the importance of factors associated with increased TP levels. RESULTS: Normal tissue TP levels correlated with histological grade (r = 0.31, P < 0.01); in patients with venous invasion or with a poor prognosis, the levels were significantly higher than in those without (P < 0.05 and < 0.001, respectively). The normal tissue TP levels were also significantly higher in the non-clear cell than in the clear cell subtype. Multiple regression analysis showed that the independent factor associated with elevated normal tissue TP levels was histological grade (R2 = 0.189, P < 0.01). There was no correlation between tumour TP and other factors. CONCLUSION: Normal tissue TP levels in localized hypervascular RCC were associated with histological grade. These data suggest that normal tissue TP levels could be a prognostic factor.

Adult↗

Prognostic factors in localized soft-tissue sarcomas.

The prognostic factors associated with local failure and overall survival and the effect of radiotherapy were determined in 77 patients with localized (extremity and nonextremity) operable soft-tissue sarcoma. There were 52 male and 25 female patients; median age was 50 years (range: 15-83). Histologic grade of the tumors was as follows: low-intermediate grade in 32 cases and high grade in 29 cases. The primary tumors were treated by marginal resection (20 patients), wide resection (52 patients), and radical resection (5 patients). Adjuvant radiotherapy was applied to 50 (65%) patients. The 5-year local recurrence-free survival rate was 70.6%. Treatment with adjuvant radiotherapy and development of metastases were the significant prognostic factors associated with local recurrence. Radiotherapy was more effective in patients with tumors 10 cm or larger, marginally resected, extremity located, and high grades. The overall survival rate was 64.4% at 5 years. Significant adverse prognostic factors were high grade tumors, presence of local recurrence, and development of metastases in univariate analyses. Development of metastases and old age were the only adverse prognostic factors by multivariate analysis. The best 5-year survival rate was obtained in female patients younger than 50 years (90%). The present study demonstrated the importance of adjuvant radiotherapy and development of metastases as prognostic factors for local control. Again, development of metastases and age were the most important prognostic factors in operable soft-tissue sarcomas.

Adolescent↗

[Prognostic factors in patients with small cell lung cancer].

OBJECTIVE: To investigate the prognostic factors of small cell lung cancer (SCLC) and establish a reliable model of clinical prognostic index. METHODS: Kaplan-Meier and Cox regression were used to analyze the relationship between survival time and prognostic factors in 60 cases of SCLC. The prognostic factors included clinical and laboratory parameters, serum cytokeratin fragment 19 (CYFRA21-1), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), CA125, interleukin-2 (IL-2) and soluble interleukin-2 receptors (sIL-2R). RESULTS: Kaplan-Meier analysis showed that poor prognosis was in patients with KPS < 80 or extensive disease and unrelated to other clinical parameters such as age, sex and smoking index, and in patients with serum NSE > 30 micro g/L, CEA > 5.0 micro g/L, CA125 > 37 KU/L and sIL-2R > 500 KU/L. Serum IL-2 and CYFRA21-1 were also elevated, but had no significant prognostic value. Multivariate analysis indicated that serum NSE, stage and treatment of disease were independent prognostic factors. The three prognostic factors enabled establishment of a prognostic index (PI) based on a simple algorithm: PI = NSE (0 if < or = 30 micro g/L, 1 if > 30 microg/L) + stage (0 = LD, 1 = ED) + CEA (0 if < or = 5.0 microg/L, 1 if > 5.0 microg/L). CONCLUSION: The stage of disease, systemic treatment and the level of serum NSE are independent prognostic factors. Without considering the influence of treatment-related factors on survival, the levels of serum CEA, NSE and stage of disease before treatment are significant independent prognostic factors. PI calculated on the basis of CEA, NSE and stage is recommended to predict the survival of SCLC.

Adult↗

Prognostic factors in elderly patients with non-Hodgkin's lymphoma treated with cyclophosphamide, vincristine, prednisone, bleomycin, Adriamycin, procarbazine (COP-BLAM) therapy.

Elderly patients with non-Hodgkin's lymphoma (NHL) were treated with cyclophosphamide, vincristine, prednisone, bleomycin, Adriamycin, procarbazine (COP-BLAM) therapy at our institution. Prognostic factors were analyzed in 62 patients with untreated NHL aged 65 years or older. Of these patients, 47 (75.8%) achieved a complete remission and 11 (17.7%) partial remission. The overall response rate was 93.5%, with a 5-year survival rate of 70%. Factors with prognostic significance included age, performance status, albumin, stage, B symptoms, and histologic type according to the International Working Formulation. Of the 62 patients, 26 were alive at the time of writing. Of the 36 patients who died, 30 died due to progression of NHL or treatment-related disorders, and 6 died from disease other than NHL. Some of the prognostic factors identified in these elderly patients are not included among the prognostic factors reported for younger patients, suggesting the need to individualize chemotherapy for NHLs of different types, which can be defined by prognostic factors. Prognostic factors other than age should be taken into account, particularly when doses and dosing intervals are determined.

Aged↗

Serum albumin as a significant prognostic factor for patients with gastric carcinoma.

BACKGROUND: The definition of prognostic factors in gastric carcinoma (GC) remains controversial. The potential of serum albumin as a prognostic factor for GC is emphasized because the technique to measure it is simple as well as being cheap and widely available. Our aim was to define the prognostic role of serum albumin in GC. METHODS: A cohort treated from January 1987 to December 2002 was studied. Relevant clinical, pathological and therapeutic variables were recorded. Kaplan-Meier and Cox's methods were used to define prognostic factors associated with cancer-related survival. RESULTS: One thousand and twenty-three patients were included. Serum albumin did impact survival, showing a dose-response effect. This effect was present after adjustment for other prognostic factors, including Tumor-Node-Metastasis (TNM) stage, surgical resection and type of lymphadenectomy. In multivariate analysis, TNM stage [Stage Ia and Ib Hazard Ratio [HR] 1, Stage II HR 1.6 (95% confidence interval [CI], 0.56-4.7), Stage IIIa HR 4.4 (95% CI 1.7-11.3), Stage IIIb HR 5.6 (95% CI 2.6-17.2), Stage IV HR 6.8 (95% CI 2.7-17.5), high albumin HR 1, medium albumin HR 1.2 (95% CI 0.8-1.7), low albumin HR 1.2 (95% CI 0.8-1.8), very low albumin HR 1.8 (95% CI 1.3-2.6), D2 dissection HR 1, D1 dissection HR 1.9 (95% CI 1.3-2.97), and no resection HR 3.7 (95% CI 2.4-5.7)] were the most significant prognostic factors associated to survival (model P = 0.00001). CONCLUSION: Pretherapeutic serum albumin level is a significant prognostic factor, which should be evaluated along with other well-defined prognostic factors in decisions concerning therapy for GC.

Adult↗

Short-term prognostic factors in lumbar disc surgery: the low back prognostic score is of predictive value.

In order to determine prognostic factors of lumbar disc surgery, we examined 107 patients who were conventionally operated on in a prospective, consecutive study. We analysed general data, the case history, the neurological examination at admission and all data from imaging examinations and therapy. In addition, all patients received a questionnaire based on the Low Back Outcome Score [9, 10]. The patients were re-examined after 2-8 months (103 days mean). According to their ratings on a pain grading scale, the patients were divided into a group with favorable and another with unfavorable results. These groups were analysed in relation to the patients' initial condition. At follow up, 88% of the patients had either completely recovered or their complaints had been relieved. According to the Low Back Outcome Score (LBOS), 64.5% went well. Used to evaluate the initial condition of the patients on admission the LBOS was able to predict favorable outcome in 68% and unfavorable outcome in 50%. To improve the prognostic value, we combined significant questions of the LBOS with the pain grading scale and significant prognostic factors to form a new prognostic score (Low Back Prognostic Score). With this new score we were able to predict a favorable outcome in 84% of our patients, and an unfavorable outcome in 71%. The Low Back Prognostic score seems to provide a sensitive method for predicting a favorable or unfavorable outcome for patients scheduled to undergo lumbar disc surgery.

Adolescent↗

[Prognostic factors in unresectable lung cancer].

Seventy-seven prognostic factors influencing survival time in patients with unresectable lung cancer treated from 1964 to 1983 at Aichi Cancer Center Hospital were analyzed using univariate analysis by log rank test and multivariate analysis by proportional hazard model of Cox. Statistical significance using univariate analysis was identified in 19 factors in small cell lung cancer patients, and in 40 factors in non-small cell lung cancer patients. The string prognostic factors determined by multivariate analysis were, in the order of importance, serum LDH level, chest pain, peripheral lymphocyte count, bone marrow metastasis, brain metastasis, age, and performance status in small cell lung cancer patients. These 7 factors had a p value of less than 0.01. On the other hand, they were the number of metastatic sites, performance status, serum albumin level, serum LDH level, sex, BUN level, N category according to TNM staging system in non-small cell lung cancer patients, with a p value of less than 0.001. The most important prognostic factors were serum LDH level in small cell lung cancer, and the number of metastatic sites and performance status in non-small cell lung cancer. A metastasis to bone marrow or brain was a more important prognostic factor than overall M category in small cell lung cancer patients, and the number of metastatic sites rather than clinical stage classification or TNM staging system in non-small cell lung cancer patients with respect to staging system. Accurate evaluation of the treatment results in unresectable lung cancer patients must take the strong prognostic factors into account.

Aged↗

Prognostic factors and survival in malignant pleural mesothelioma.

Malignant pleural mesothelioma is a lethal disease and little is known about prognostic factors. The prognostic significance of age, stage of disease, gender and histological subtype was studied in 167 new cases of cytologically (15%) or histologically (85%) proven malignant pleural mesothelioma in the Rotterdam area, during the period 1987-1989. Median survival of all patients was 242 days. Univariate analysis identified age, stage and histopathological subtype as significant prognostic factors, which was confirmed in multivariate analysis. Median survival rates for patients < 65, 65-74 and > or = 75 yrs were 359, 242 and 131 days, respectively. Patients with Stage I disease had a median survival of 359 days compared to 147 and 112 days, respectively, for patients with Stage II and the combination of Stages III and IV. Mixed histopathological subtype (190 days) was less favourable than sarcomatous (207 days) and epithelial (252 days) subtypes. Using a Cox proportional hazard model in patients with malignant pleural mesothelioma, age, histological subtype and stage were identified as independent prognostic factors. These prognostic factors should be taken into account when starting or evaluating treatment studies.

Age Factors↗

[An overview of new prognostic factors in lung cancer].

The knowledge of prognostic factors such as TNM, performance status, and sex is essential for predicting patient outcome and optimal trial design and analysis. Recent advances in cytogenetics and molecular biology have yielded new prognostic factors such as DNA ploidy, oncogenes and oncogene product. New prognostic factors can predict patient outcome and should be incorporated for the multivariate analysis of prognostic factors. They can provide a guideline for selecting special patient population suitable for adjuvant chemotherapy even in the early stage of lung cancer.

ABO Blood-Group System↗

[Prognostic factors in low-grade lymphoma].

PURPOSE: Prognostic factors in low grade non-Hodgkin's lymphoma (LGL) are not well established. The aim of this study is to investigate prognostic factors on LGL treated in our institution during the last decade. PATIENTS AND METHODS: The study was carried out on 70 cases of newly diagnosed LGL, most treated with CVP or clorambucil and prednisone. The median follow-up was 37 months (1-132). Variables reported as prognostic factors in previous series were subjected to bivariate and multivariate analysis. RESULTS: Relevant clinical features were: Ann Arbor III-IV stage 74%, ECOG > or = 2-17%, bone marrow involvement 60% and large tumor burden according to MD Anderson criteria 21%. Complete response (CR) was achieved in 50% and partial response in 29%. In bivariate analysis factors related with poor CR were B symptoms, large tumor burden, high LDH and more than one extranodal site involvement. Logistic regression showed that large tumor burden (p = 0.02; OR = 0.07) and B symptoms (p = 0.07; OR = 0.14) were the best prognostic factors of poor CR. Five year global survival (GS) was 55%, with a median of 76 months. In univariate analysis factors related with GS were ECOG > or = 2, B symptoms, bulky, large tumor burden, retroperitoneo involvement and absence of CR. In multivariate analysis the only factor related with poor GS was large tumor burden (p < 0.00001; RR = 5.93). When therapeutic response was included in the model, absence of CR (p = 0.008; RR = 3.40) and large tumour burden (p = 0.005; RR = 3.86) were the factors selected. CONCLUSIONS: In LGL tumor burden was the most important prognostic variable. Tumor response showed less importance than in high grade lymphomas.

Adult↗

[Multivariate analysis of prognostic factors in colorectal cancer patients with different ages].

OBJECTIVE: To investigate the prognostic factors of young, middle-age and old-age colorectal cancer patients in order to improve the treatment in the future. METHODS: Colorectal cancer patients (n = 842) who had undergon curative resection were divided into three groups according their age: young group (< or = 40 years), middle-age group (41 to 64 years) and old group (> o = 65 years). Thirty-five clinical factors in the three groups were analyzed and compared by univariate survival and multivariate analysis. Cox proportional hazards regression model was used with SPSS statistic software. RESULTS: The overall 5-, 10- and 15-year survival rates were 66.3%, 54.2% and 48.5% respectively. The 5- and 10-year survival rates were 53.0% and 42.7% in the young group, which were lower than those in the other two groups. Cox proportional hazards regression model demonstrated that Dukes stage and family history of cancer were common prognostic factors in both young and middle-age groups; chronic constipation was an independent prognostic factor in middle-age group; bowel obstruction, length of operating time and number of metastatic lymph nodes were prognostic factors in the older group. In the young group, the symptomatic duration was not demonstrated as a prognostic factor. The 5- and 10-year survival rates were 82.6% and 64.5% in Dukes A stage; 73.3% and 67.4% in B stage; 37.3% and 27.0% in C stage; 33.3% and 22.2% in D stage. The survival rates in Dukes A and B stages were similar, but in Dukes C and D stages they were lower than those of the middle-age and older groups if the patient had the same stage of disease. In the young colorectal cancer patients with family cancer history, the 5- and 10-year survival rates were 73.1% and 64.5%, which were better than those of patients without it (48.1% and 37.3%). CONCLUSION: In young colorectal cancer patients, the survival rate is lower than those in the middle-age and old patients. Family cancer history and/or advanced Dukes stage are poor prognostic factors, whereas the symptomatic duration is not demonstrated as a poor prognostic factor. The prognostic factors affecting the survival after surgical treatment may be different in different age groups of colorectal cancer patients.

Adult↗

Prognostic factors: guidelines for investigation design and state of the art analytical methods.

The proliferation of putative prognostic factors, derived prognostic indices and computerised prediction of outcome in surgical oncology has led to some confusion over the exact methods available for deriving clinically significant prognostic factors. The realisation that the interaction between factors is often complex and non-linear has led to the development of new statistical techniques. The aim of this article is to review the currently available methods of analysis. A review of the relevant literature available from statistical, medical and computer science sources was performed. Information has been conveyed at a level aimed at producing a practical understanding of the techniques involved rather than their underlying mathematical basis. There are now clear guidelines for the investigation of putative prognostic factors (Table 1). The established role of linear statistical models and prognostic indices remains vitally important for the majority of diseases with many derived prognostic indices having been validated in a prospective fashion. However, in order to improve the delineation of prognostic factors other more complex methods of analysis are now being utilised. Furthermore, the recognition of complex dynamic non-linearity within biological systems has led to the increasing use of non-linear statistical techniques and artificial intelligence. As such it is incumbent upon the modern clinician to be able to understand the basic assumptions required for multivariate analysis and also to realise when alternative statistical techniques should be employed.

Artificial Intelligence↗