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PubMed2004

Effect of prize draw incentive on the response rate to a postal survey of obstetricians and gynaecologists: a randomised controlled trial. [ISRCTN32823119].

BACKGROUND: Response rates to postal questionnaires are falling and this threatens the external validity of survey findings. We wanted to establish whether the incentive of being entered into a prize draw to win a personal digital assistant (PDA) would increase the response rate for a national survey of consultant obstetricians and gynaecologists. METHODS: A randomised controlled trial was conducted. This involved sending a postal questionnaire to all Consultant Obstetricians and Gynaecologists in the United Kingdom. Recipients were randomised to receiving a questionnaire offering a prize draw incentive (on response) or no such incentive. RESULTS: The response rate for recipients offered the prize incentive was 64% (461/716) and 62% (429/694) in the no incentive group (relative rate of response 1.04, 95% CI 0.96 - 1.13) CONCLUSION: The offer of a prize draw incentive to win a PDA did not significantly increase response rates to a national questionnaire survey of consultant obstetricians and gynaecologists.

Computers, Handheld↗
PubMed2025

LungGENIE: the lung gene-expression and network imputation engine.

BACKGROUND: Few cohorts have study populations large enough to conduct molecular analysis of ex vivo lung tissue for genomic analyses. Transcriptome imputation is a non-invasive alternative with many potential applications. We present a novel transcriptome-imputation method called the Lung Gene Expression and Network Imputation Engine (LungGENIE) that uses principal components from blood gene-expression levels in a linear regression model to predict lung tissue-specific gene-expression. METHODS: We use paired blood and lung RNA sequencing data from the Genotype-Tissue Expression (GTEx) project to train LungGENIE models. We replicate model performance in a unique dataset, where we generated RNA sequencing data from paired lung and blood samples available through the SUNY Upstate Biorepository (SUBR). We further demonstrate proof-of-concept application of LungGENIE models in an independent blood RNA sequencing data from the Genetic Epidemiology of COPD (COPDGene) study. RESULTS: We show that LungGENIE prediction accuracies have higher correlation to measured lung tissue expression compared to existing cis-expression quantitative trait loci-based methods (median Pearson's r = 0.25, IQR 0.19-0.32), with close to half of the reliably predicted transcripts being replicated in the testing dataset. Finally, we demonstrate significant correlation of differential expression results in chronic obstructive pulmonary disease (COPD) from imputed lung tissue gene-expression and differential expression results experimentally determined from lung tissue. CONCLUSION: Our results demonstrate that LungGENIE provides complementary results to existing expression quantitative trait loci-based methods and outperforms direct blood to lung results across internal cross-validation, external replication, and proof-of-concept in an independent dataset. Taken together, we establish LungGENIE as a tool with many potential applications in the study of lung diseases.

Humans↗
PubMed2025

Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis.

BACKGROUND: Palmitoylation, a post-translational lipid modification, has garnered increasing attention for its role in inflammatory processes and tumorigenesis. Emerging evidence suggests a potential association between palmitoylation and inflammatory responses in the pathogenesis of endometriosis. However, the precise mechanistic interplay remains elusive, necessitating further investigation. METHODS: This study integrated transcriptomic analysis and Mendelian randomization (MR) to identify a causal gene set implicated in endometriosis. Differentially expressed genes (DEGs) were first identified in the training dataset using the limma package in R. Weighted gene co-expression network analysis (WGCNA) was subsequently performed, leveraging Single Sample Gene Set Enrichment Analysis (ssGSEA)-derived scores of palmitoylation-related genes (PRGs) as phenotypic traits to identify key modular genes. The intersection of these key modular genes with DEGs yielded a refined gene set. Machine learning algorithms were then applied to further optimize gene selection, followed by external validation, immune infiltration analysis, RNA network construction, and exploration of potential targeted drug candidates. RESULTS: Through a rigorous screening process, VRK1, GALNT12, and RMI1 emerged as key genes associated with palmitoylation, exhibiting significant downregulation in endometriosis samples (P <&#x2009;0.05), indicative of a potential protective role. Immune infiltration analysis further revealed strong correlations between these genes and M2 macrophages as well as resting Natural Killer (NK) cells. Additionally, investigations into the targeted RNA network and drug association profiling provided novel insights, laying the groundwork for future high-quality validation studies. CONCLUSIONS: This study employed a comprehensive analytical framework to identify palmitoylation-associated key genes in endometriosis. The integration of immunoinfiltration analysis, RNA network construction, and drug association profiling offers valuable insights for advancing clinical diagnostics, disease monitoring, and therapeutic development in endometriosis.

Humans↗
PubMed2025

Construction of a prognostic model for gastric cancer based on immune infiltration and microenvironment, and exploration of MEF2C gene function.

BACKGROUND: Advanced gastric cancer (GC) exhibits a high recurrence rate and a dismal prognosis. Myocyte enhancer factor 2c (MEF2C) was found to contribute to the development of various types of cancer. Therefore, our aim is to develop a prognostic model that predicts the prognosis of GC patients and initially explore the role of MEF2C in immunotherapy for GC. METHODS: Transcriptome sequence data of GC was obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and PRJEB25780 cohort for subsequent immune infiltration analysis, immune microenvironment analysis, consensus clustering analysis and feature selection for definition and classification of gene M and N. Principal component analysis (PCA) modeling was performed based on gene M and N for the calculation of immune checkpoint inhibitor (ICI) Score. Then, a Nomogram was constructed and evaluated for predicting the prognosis of GC patients, based on univariate and multivariate Cox regression. Functional enrichment analysis was performed to initially investigate the potential biological mechanisms. Through Genomics of Drug Sensitivity in Cancer (GDSC) dataset, the estimated IC50 values of several chemotherapeutic drugs were calculated. Tumor-related transcription factors (TFs) were retrieved from the Cistrome Cancer database and utilized our model to screen these TFs, and weighted correlation network analysis (WGCNA) was performed to identify transcription factors strongly associated with immunotherapy in GC. Finally, 10 patients with advanced GC were enrolled from Sun Yat-sen University Cancer Center, including paired tumor tissues, paracancerous tissues and peritoneal metastases, for preparing sequencing library, in order to perform external validation. RESULTS: Lower ICI Score was correlated with improved prognosis in both the training and validation cohorts. First, lower mutant-allele tumor heterogeneity (MATH) was associated with lower ICI Score, and those GC patients with lower MATH and lower ICI Score had the best prognosis. Second, regardless of the T or N staging, the low ICI Score group had significantly higher overall survival (OS) compared to the high ICI Score group. For its mechanisms, consistently, for Camptothecin, Doxorubicin, Mitomycin, Docetaxel, Cisplatin, Vinblastine, Sorafenib and Paclitaxel, all of the IC50 values were significantly lower in the low ICI Score group compared to the high ICI Score group. As a result, based on univariate and multivariate Cox regression, ICI Score was considered to be an independent prognostic factor for GC. And our Nomogram showed good agreement between predicted and actual probabilities. Based on CIBERSORT deconvolution analysis, there was difference of immune cell composition found between high and low ICI Score groups, probably affecting the efficacy of immunotherapy. Then, MEF2C, a tumor-related transcription factor, was screened out by WGCNA analysis. Higher MEF2C expression is significantly correlated with a worse OS. Moreover, its higher expression is also negatively correlated with tumor mutation burden (TMB) and microsatellite instability (MSI), but positively correlated with several immunosuppressive molecules, indicating MEF2C may exert its influence on tumor development by upregulating immunosuppressive molecules. Finally, based on transcriptome sequencing data on 10 paired tumor tissues from Sun Yat-sen University Cancer Center, MEF2C expression was significantly lower in paracancerous tissues compared to tumor tissues and peritoneal metastases, and it was also lower in tumor tissues compared to peritoneal metastases, indicating a potential positive association between MEF2C expression and tumor invasiveness. CONCLUSIONS: Our prognostic model can effectively predict outcomes and facilitate stratification GC patients, offering valuable insights for clinical decision-making. The identified transcription factor MEF2C can serve as a biomarker for assessing the efficacy of immunotherapy for GC.

Humans↗
PubMed2026

Targeting RELA and STAT3 regulates TNFRSF10A-mediated apoptosis in a novel apoptosis-based prognostic model for clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal malignancy and remains a major cause of cancer-related mortality worldwide. Although advances in surgery, targeted therapy, and immunotherapy have improved outcomes for patients, reliable biomarkers for predicting prognosis remain limited. Therefore, robust gene-based prognostic models are urgently needed to improve risk stratification and guide individualized treatment strategies. METHODS: We developed a novel prognostic model integrating apoptosis and immune - related genes (AIRGs) to predict overall survival (OS) in patients with ccRCC. RESULT: Using Gene Set Enrichment Analysis (GSEA) combined with least absolute shrinkage and selection operator (LASSO) Cox regression, we identified 7 key prognostic genes, namely, CCR4, TNFRSF10A, TEK, TGFA, CD14, IFITM1, and SEMA3G, that collectively demonstrated strong predictive performance in TCGA cohort with c-index&#x2009;=&#x2009;0.711. Functional enrichment analyses revealed that apoptosis, immune regulation, and multiple oncogenic signaling pathways were significantly associated with the risk score, highlighting the critical role of the tumor microenvironment in ccRCC progression. Transcription factor binding analysis based on the JASPAR database suggested that RELA and STAT3 with scores of 0.829 and 0.951, respectively are potential upstream regulators within the prognostic network, particularly influencing TNFRSF10A expression. External validation using the International Cancer Genome Consortium (ICGC) dataset confirmed the robustness of the prognostic model with c-index&#x2009;=&#x2009;0.612 Furthermore, in vitro experiments demonstrated that RELA and STAT3 regulate TNFRSF10A-mediated apoptotic signaling in ccRCC cells, providing mechanistic support for the bioinformatic findings. CONCLUSION: This study establishes a biologically informed and clinically relevant prognostic framework for ccRCC. Our findings highlight the therapeutic potential of targeting the RELA/STAT3-TNFRSF10A axis and contribute to the advancement of precision medicine in ccRCC.

Humans↗
PubMed2025

Genetic and transcriptional insights into immune checkpoint blockade response and survival: lessons from melanoma and beyond.

BACKGROUND: Integration of immune checkpoint inhibitors (ICIs) with non-immune therapies relies on identifying combinatorial biomarkers, which are essential for patient stratification and personalized treatment. METHODS: We analyzed genomic and transcriptomic data from pretreatment tumor samples of 342 melanoma patients treated with ICIs to identify mutations and expression signatures associated with ICI response and survival. External validation and mechanistic exploratory analyses were conducted in two additional datasets to assess generalizability. RESULTS: Responders were more likely to have received anti-PD-1 therapy rather than anti-CTLA-4 and exhibited a higher tumor mutation burden (both P&#x2009;<&#x2009;0.001). Mutations in the dynein axonemal heavy chain (DNAH) family genes, specifically DNAH2 (P&#x2009;=&#x2009;0.03), DNAH6 (P&#x2009;<&#x2009;0.001), and DNAH9 (P&#x2009;<&#x2009;0.01), were enriched in responders. The combined mutational status of DNAH 2/6/9 effectively stratified patients by progression-free survival (hazard ratio [HR]: 0.69; 95% confidence interval [CI] 0.51-0.92; P&#x2009;=&#x2009;0.013) and overall survival (HR: 0.58; 95% CI 0.43-0.78; P&#x2009;<&#x2009;0.001), with consistent association observed in the validation cohort (HR: 0.28; 95% CI 0.12-0.61; P&#x2009;<&#x2009;0.001). DNAH-altered melanomas exhibited upregulation of chemokine signaling, cytokine-cytokine receptor interaction, and cell cycle-related pathways, along with elevated expression of immune-related signatures in interferon signaling, cytolytic activity, T cell function, and immune checkpoints. Using LASSO logistic regression, we identified a 26-gene composite signature predictive of clinical response, achieving an area under the curve (AUC) of 0.880 (95% CI 0.825-0.936) in the training dataset and 0.725 (95% CI 0.595-0.856) in the testing dataset. High-risk patients, stratified by the expression levels of a 13-gene signature, demonstrated significantly shorter overall survival in both datasets (HR: 3.35; P&#x2009;<&#x2009;0.001; HR: 2.93; P&#x2009;=&#x2009;0.002). CONCLUSIONS: This analysis identified potential molecular determinants of response and survival to ICI treatment. Insights from melanoma biomarker research hold significant promise for translation into other malignancies, guiding individualized anti-tumor immunotherapy.

Humans↗
PubMed2025

Integrative multi-omics analysis proposes a metabolic classification of gliomas: distinct metabolic states, immune infiltration, and prognosis.

BACKGROUND: The tumor microenvironment (TME) of glioma harbors diverse cell types; however, cell metabolic heterogeneity remains to be explored. This study aims to characterize the metabolic features of different cell types in the TME by integrating multiple datasets, including genomics, bulk and single-cell transcriptomics, and metabolomics. METHODS: Unsupervised machine learning was used to construct an energy metabolic classifier based on the metabolic pathways identified from bulk RNA-seq of gliomas in the TCGA dataset. The classifier was externally validated using multiple datasets, including genomics, bulk RNA-seq, snRNA-seq, and the metabolomics data. Furthermore, metabolic heterogeneity associated with the classifier was further characterized at single-cell resolution. RESULTS: The energy metabolism-based classifier stratified patients into two prognostic clusters: patients in cluster 1 were characterized by high pathway activity of glycolysis, the pentose phosphate pathway (PPP), and fatty acid oxidation (FAO), whereas patients in cluster 2 exhibited higher activity in glutaminolysis. This metabolic classifier revealed both intratumoral and intertumoral metabolic heterogeneity, and the complexity was further validated by the metabolomics profiling and snRNA-seq data from the CPTAC dataset. Notably, OSMR, highly expressed in cluster 1, showed significant co-expression with key glycolytic enzyme genes. The OSM/OSMR/JAK1/STAT3 axis potently drives malignant progression of glioma cells, specially enhancing their invasive and migratory capabilities. Single-cell resolution analyses demonstrated that tumor metabolic heterogeneity is primarily driven by malignant cells rather than non-malignant components, while tumor microenvironment (TME) factors were also found to modulate malignant cell metabolism. Significantly, glycolytic activity in glioma cells increased during the phenotypic transition from PN (proneural) to MES (mesenchymal), with cluster 1 metabolic phenotypes predominating in the tumor core. Compared to cluster 2, cluster 1 patients exhibited higher mRNA expression of immunosuppressive checkpoint genes, which correlated with pronounced immunosuppression in the TME. Furthermore, various immune cells demonstrated distinct metabolic preferences at single-cell resolution. CONCLUSIONS: This study developed an energy metabolic-based classifier for gliomas with prognostic and therapeutic potential. Metabolic reprogramming was linked with the PN-to-MES transition of glioma cells and immunosuppression in the tumor microenvironment. Multi-omics data, especially snRNA-seq, offered insights into metabolism heterogeneity at single-cell resolution, enabling personalized treatment strategies.

Humans↗
PubMed2003

Prognostic factors for ambulation and activities of daily living in the subacute phase after stroke. A systematic review of the literature.

OBJECTIVE: To identify evidence-based prognostic factors in the subacute phase after stroke for activities of daily living (ADL) and ambulation at six months to one year after stroke. DESIGN: Systematic literature search designed in accordance with the Cochrane Collaboration criteria with the following data sources: (1) MEDLINE, EMBASE, CINAHL, Current Contents, Cochrane Database of Systematic Reviews, Psyclit, and Sociological Abstracts. (2) Reference lists, personal archives, and consultation of experts. (3) Guidelines. METHODS: Inclusion criteria were: (1) cohort studies of patients with an ischaemic or haemorrhagic stroke; (2) inception cohort with assessment of prognostic factors within the first two weeks after stroke; (3) outcome measures for ADL and ambulation; and (4) a follow-up of six months to one year. Internal, statistical and external validity of the studies were assessed using a checklist with 11 methodological criteria in accordance with the recommendations of the Cochrane Collaboration. RESULTS: From 1,027 potentially relevant studies 26 studies involving a total of 7,850 patients met the inclusion criteria. Incontinence for urine is the only prognostic factor identified in three studies with a level A (i.e., a good level of scientific evidence according to the methodological score). The following factors were found in one level A study: initial ADL disability and ambulation, high age, severe paresis or paralysis, impaired swallowing, ideomotor apraxia, ideational apraxia, and visuospatial construction problems; as well as factors relating to complications of an ischaemic stroke, such as extraparenchymal bleeding, cerebral oedema and size of intraparenchymal haemorrhage. CONCLUSIONS: The present evidence concerning possible predictors in the subacute stage of stroke has insufficient quality to make an evidence-based prediction of ADL and ambulation after stroke because only one prognostic factor was demonstrated in at least two level A studies, our cut-off for sufficient scientific evidence.

Activities of Daily Living↗
PubMed2003

Prognostic factors in the subacute phase after stroke for the future residence after six months to one year. A systematic review of the literature.

OBJECTIVE: To identify evidence-based prognostic factors in the subacute phase after a stroke for future residence at six months to one year post stroke. DESIGN: Systematic literature search designed in accordance with the Cochrane Collaboration criteria with the following data sources: (1) MEDLINE, EMBASE, CINAHL, Current Contents, Cochrane Database of Systematic Reviews, PsycLIT and Sociological Abstracts. (2) Reference lists, personal archives and consultation of experts in the field. (3) Guidelines. METHODS: Inclusion criteria were: (1) cohort studies of patients with an ischaemic or haemorrhagic stroke; (2) inception cohort with assessment of prognostic factors within the first two weeks after stroke; (3) outcome measures for future residence; and (4) a follow-up of six months to one year. Internal, statistical and external validity of the studies were assessed using a checklist with 11 methodological criteria in accordance with the recommendations of the Cochrane Collaboration. RESULTS: From 1027 potentially relevant studies 10 studies involving a total of 3564 patients met the inclusion criteria. No prognostic factor was identified in at least two level A (i.e., a good level of scientific evidence according to the methodological score) studies, our standard for scientific proof. The following factors were found in at least one level A study: low initial ADL functioning, high age, cognitive disturbance, paresis of arm and leg, not alert as initial level of consciousness, old hemiplegia, homonymous hemianopia, visual extinction, constructional apraxia, no transfer to the stroke unit, nonlacunar stroke type, visuospatial construction problems, urinary incontinence and female gender. CONCLUSIONS: At present there is insufficient evidence concerning possible predictors in the subacute stage of stroke to make an evidence-based prediction of the future residence. In the scientific research until now social factors and their contribution to the possibility of living independently have not been investigated, or at least less well. None of the studies in this review described a conceptual framework as basis for the choice of the examined prognostic factors.

Activities of Daily Living↗
PubMed2006

TREAD: TReatment with Exercise Augmentation for Depression: study rationale and design.

BACKGROUND: Despite recent advancements in the pharmacological treatment of major depressive disorder (MDD), over half of patients who receive treatment with antidepressant medication do not achieve full remission of symptoms. There is evidence that exercise can reduce depressive symptomatology when used as a treatment for MDD. However, no randomized controlled trials have evaluated exercise as an augmentation strategy for patients with carefully diagnosed MDD who remain symptomatic following an adequate acute phase trial of antidepressant therapy. PURPOSE: TReatment with Exercise Augmentation for Depression (TREAD) is an NIMH-funded, randomized, controlled trial designed to assess the relative efficacy of two doses of aerobic exercise to augment selective serotonin reuptake inhibitor (SSRI) treatment of MDD. METHODS: The TREAD study includes 12 weeks of acute phase treatment with a 12-week post-treatment follow-up. In addition to looking at change in depressive symptoms as a primary outcome, it also includes comprehensive assessment of psychosocial function and treatment adherence. RESULTS: This paper reviews the rationale and design of TREAD and illustrates how we address several key issues in contemporary patient-oriented research on MDD: 1) the use of augmentation strategies in the treatment of depressive disorders in general, 2) the use of non-pharmacological strategies in the treatment of depressive disorders, 3) the considerations of designing a well-controlled trial using two active treatment groups, and 4) the implementation of an adherence program for the use of exercise as a treatment strategy. CONCLUSIONS: The TREAD study is uniquely designed to overcome sources of potential bias and threats to internal and external validity that have limited prior research on the mental health effects of exercise. The study is facilitated by the development of a multidisciplinary research team that includes experts in both depression treatment and exercise physiology, as well as other related fields.

Adolescent↗
PubMed1996

Cognitive therapy and recovery from acute psychosis: a controlled trial. I. Impact on psychotic symptoms.

BACKGROUND: The application of cognitive therapy (CT) to psychosis is currently being developed in the UK. This paper reports a trial of CT in acute psychosis with the objective of hastening the resolution of positive symptoms and reducing residual symptoms. METHOD: Of 117 patients with acute non-affective psychosis, 69 satisfied inclusion criteria and 40 proceeded to stratified randomisation. The experimental intervention involving individual and group CT was compared with a group receiving matched hours of therapist input providing structured activities and informal support; routine pharmacotherapy was provided by clinicians blind to group allocation. Patients were monitored weekly using self-report and mental state assessments during admission and over the subsequent nine months. RESULTS: Both groups showed a decline in positive symptoms but this was more marked in the CT group (P < 0.001). At 9 months 5% of the CT group, v.56% of the control group, showed moderate or severe residual symptoms. CONCLUSION: CT appears to be a potent adjunct to pharmacotherapy and standard care for acute psychosis. Issues concerning internal and external validity of the study and opportunities for further research are discussed.

Acute Disease↗
PubMed2004

Study of agreement between LDL size as measured by nuclear magnetic resonance and gradient gel electrophoresis.

LDL particle size can be measured by gradient gel electrophoresis (GGE) and NMR. The agreement between the two methods has not been extensively evaluated. Therefore, we measured LDL size by NMR and GGE in 324 individuals (152 with type 1 diabetes and 172 controls). The Spearman correlation between both methods was 0.39 [95% confidence interval (CI) = 0.29, 0.48]. The average difference was 5.38 nm (NMR being smaller), but it increased with increasing LDL size. Less than 50% of people classified as pattern B on GGE were classified as pattern B on NMR (kappa = 0.31; 95% CI = 0.17, 0.45). Agreement was lower for diabetic subjects compared with controls, for women compared with men, and for subjects with triglycerides less than 1.30 mmol/l compared with subjects with triglycerides greater than 1.30 mmol/l. External validation showed that cholesteryl ester transfer rate was related to LDL size on GGE in all subgroups and to LDL size on NMR only in men and nondiabetic subjects. Our findings show that agreement between NMR- and GGE-based LDL size is far from perfect and is not consistent across subgroups of patients. In particular, the two methods should not be assumed to be interchangeable in women and diabetic subjects. Whether NMR or GGE predicts cardiovascular disease risk better has not yet been evaluated.

Adult↗
PubMed1995

Prediction of residual retroperitoneal mass histology after chemotherapy for metastatic nonseminomatous germ cell tumor: multivariate analysis of individual patient data from six study groups.

PURPOSE: To develop a statistical model that predicts the histology (necrosis, mature teratoma, or cancer) after chemotherapy for metastatic nonseminomatous germ cell tumor (NSGCT). PATIENTS AND METHODS: An international data set was collected comprising individual patient data from six study groups. Logistic regression analysis was used to estimate the probability of necrosis and the ratio of cancer and mature teratoma. RESULTS: Of 556 patients, 250 (45%) had necrosis at resection, 236 (42%) had mature teratoma, and 70 (13%) had cancer. Predictors of necrosis were the absence of teratoma elements in the primary tumor, prechemotherapy normal alfa-fetoprotein (AFP), normal human chorionic gonadotropin (HCG), and elevated lactate dehydrogenase (LDH) levels, a small prechemotherapy or postchemotherapy mass, and a large shrinkage of the mass during chemotherapy. Multivariate combination of predictors yielded reliable models (goodness-of-fit tests, P > .20), which discriminated necrosis well from other histologies (area under the receiver operating characteristic (ROC) curve, .84), but which discriminated cancer only reasonably from mature teratoma (area, .66). Internal and external validation confirmed these findings. CONCLUSION: The validated models estimate with high accuracy the histology at resection, especially necrosis, based on well-known and readily available predictors. The predicted probabilities may help to choose between immediate resection of a residual mass or follow-up, taking into account the expected benefits and risks of resection, feasibility of frequent follow-up, the financial costs, and the patient's individual preferences.

Analysis of Variance↗
PubMed1998

1997 update of recommendations for the use of tumor markers in breast and colorectal cancer. Adopted on November 7, 1997 by the American Society of Clinical Oncology.

OBJECTIVE: The primary objective was to update the 1996 clinical practice guidelines for the use of tumor marker tests in the prevention, screening, treatment, and surveillance of breast and colorectal cancers. These guidelines are intended for use in the care of patients outside of clinical trials. OPTIONS: Six tumor markers for colorectal cancer and eight for breast cancer were considered. They could be recommended or not for routine use or for special circumstances. In addition to carcinoembryonic antigen (CEA) and cancer antigen (CA) 15-3, CA 27.29 also was considered in regard to circulatory tumor markers for breast cancer. OUTCOMES: In general, the significant health outcomes identified for use in making clinical practice guidelines (overall survival, disease-free survival, quality of life, lesser toxicity, and cost effectiveness) were used. EVIDENCE: A computerized literature search from 1994 to July 1997 was performed. VALUES: The same values for Use, Utility, and Levels of Evidence were used by the Committee. BENEFITS, HARMS, AND COSTS: The same benefit, harms, and costs were used. RECOMMENDATION: No changes in any guidelines were recommended (see text). VALIDATION: External review by the American Society of Clinical Oncology (ASCO) Health Services Research Committee and by ASCO Board of Directors. SPONSOR: American Society of Clinical Oncology.

Biomarkers, Tumor↗
PubMed1999

Randomized phase III study of gemcitabine-cisplatin versus etoposide-cisplatin in the treatment of locally advanced or metastatic non-small-cell lung cancer.

PURPOSE: We conducted a randomized trial to compare gemcitabine-cisplatin with etoposide-cisplatin in the treatment of patients with advanced non-small-cell lung cancer (NSCLC). The primary end point of the comparison was response rate. PATIENTS AND METHODS: A total of 135 chemotherapy-naive patients with advanced NSCLC were randomized to receive either gemcitabine 1,250 mg/m2 intravenously (IV) days 1 and 8 or etoposide 100 mg/m2 IV days 1 to 3 along with cisplatin 100 mg/m2 IV day 1. Both treatments were administered in 21-day cycles. One hundred thirty-three patients were included in the intent-to-treat analysis of response. RESULTS: The response rate (externally validated) for patients given gemcitabine-cisplatin was superior to that for patients given etoposide-cisplatin (40.6% v 21.9%; P = .02). This superior response rate was associated with a significant delay in time to disease progression (6.9 months v 4.3 months; P = .01) without an impairment in quality of life (QOL). There was no statistically significant difference in survival time between both arms (8.7 months for gemcitabine-cisplatin v 7.2 months for etoposide-cisplatin; P = .18). The overall toxicity profile for both combinations of drugs was similar. Nausea and vomiting were reported more frequently in the gemcitabine arm than in the etoposide arm. However, the difference was not significant. Gemcitabine-cisplatin produced less grade 3 alopecia (13% v 51%) and less grade 4 neutropenia (28% v 56% ) but more grade 3 and 4 thrombocytopenia (56% v 13%) than did etoposide-cisplatin. However, there were no thrombocytopenia-related complications in the gemcitabine arm. CONCLUSION: Compared with etoposide-cisplatin, gemcitabine-cisplatin provides a significantly higher response rate and a delay in disease progression without impairing QOL in patients with advanced NSCLC.

Adult↗
PubMed2001

Patterns of use of chemotherapy for breast cancer in older women: findings from Medicare claims data.

PURPOSE: There is little population-based information available on the use of chemotherapy in women with breast cancer. This study describes the use of chemotherapy through analysis of Medicare claims and determines the correlates of chemotherapy use. PATIENTS AND METHODS: We used the merged Surveillance, Epidemiology, and End Results-Medicare database and identified women > or = 65 years of age diagnosed with breast cancer in 1991 and 1992. Chemotherapy was ascertained from Medicare claims through procedure codes for chemotherapy made within 24 months of the diagnosis. RESULTS: In women with stages I, II, III, and IV breast cancer, the percentage receiving chemotherapy within 24 months of diagnosis was 5.1%, 19.5%, 33.9%, and 35.2%, respectively. Most women receiving chemotherapy had two to 12 claims; the median number was eight. Use of chemotherapy decreased significantly with age across all tumor stages; eg, in women with stage III cancer, the use of chemotherapy declined from 49% in those aged 65 to 69 years to 10% in those > or = 80 years old. In a multivariate analysis, there was little variation by ethnicity. Chemotherapy use was highest (70%) in women aged 65 to 69 years with node-positive and estrogen receptor-negative tumors and lowest (5%) in those with node-negative and estrogen receptor-positive tumors. Compared with those without comorbid diseases, patients with a comorbidity score of 2 had significantly lower use of chemotherapy. CONCLUSION: Medicare claims data seem to provide valuable information on the use of chemotherapy for breast cancer in older women. However, external validation of the accuracy and completeness of these data is required before any firm conclusion can be drawn.

Age Factors↗
PubMed2006

Primary central nervous system lymphoma: the Memorial Sloan-Kettering Cancer Center prognostic model.

PURPOSE: The purpose of this study was to analyze prognostic factors for patients with newly diagnosed primary CNS lymphoma (PCNSL) in order to establish a predictive model that could be applied to the care of patients and the design of prospective clinical trials. PATIENTS AND METHODS: Three hundred thirty-eight consecutive patients with newly diagnosed PCNSL seen at Memorial Sloan-Kettering Cancer Center (MSKCC; New York, NY) between 1983 and 2003 were analyzed. Standard univariate and multivariate analyses were performed. In addition, a formal cut point analysis was used to determine the most statistically significant cut point for age. Recursive partitioning analysis (RPA) was used to create independent prognostic classes. An external validation set obtained from three prospective Radiation Therapy Oncology Group (RTOG) PCNSL clinical trials was used to test the RPA classification. RESULTS: Age and performance status were the only variables identified on standard multivariate analysis. Cut point analysis of age determined that patients age < or = 50 years had significantly improved outcome compared with older patients. RPA of 282 patients identified three distinct prognostic classes: class 1 (patients < 50 years), class 2 (patients > or =50; Karnofsky performance score [KPS] > or = 70) and class 3 (patients > or = 50; KPS < 70). These three classes significantly distinguished outcome with regard to both overall and failure-free survival. Analysis of the RTOG data set confirmed the validity of this classification. CONCLUSION The MSKCC prognostic score is a simple, statistically powerful model with universal applicability to patients with newly diagnosed PCNSL. We recommend that it be adopted for the management of newly diagnosed patients and incorporated into the design of prospective clinical trials.

Adult↗
PubMed2004

The future of health behavior change research: what is needed to improve translation of research into health promotion practice?

BACKGROUND: It is well documented that the results of most behavioral and health promotion studies have not been translated into practice. PURPOSE: In this article, reasons for this gap, focusing on study design characteristics as a central contributing barrier, are discussed. METHODS: Four reviews of recent controlled studies in work sites, health care, school, and community settings are briefly discussed and summarized. Their implications for future research and for closing the gap between research and practice are then discussed. RESULTS: These reviews come to consistent conclusions regarding key internal and external validity factors that have and have not been reported. It is very clear that moderating variables and generalization issues have not been included or reported in the majority of investigations, and that as a consequence little is known about the representatives or the robustness of results from current studies. CONCLUSIONS: To significantly improve the current state of affairs, substantial changes will be required on the part of researchers, funding agencies, and review and editorial boards. In conclusion, recommendations for each of these entities are provided.

Algorithms↗