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At least 307 records · Page 17Linked to original sources
PubMed2005

Three-dimensional power Doppler vascular sampling: a new method for predicting ovarian cancer in vascularized complex adnexal masses.

OBJECTIVE: The purpose of this study was to explore the role of a new concept ("vascular sampling") as a third step to discriminate benign and malignant lesions in B-mode and color Doppler sonographically suggestive adnexal masses. METHODS: Forty-five women (mean age, 52.3 years; range, 17-82 years) with the diagnosis of complex adnexal masses on B-mode sonography were evaluated using 3-dimensional power Doppler sonography. Four women had bilateral masses. After a morphologic reevaluation was done, color pulsed Doppler sonography was used to obtain flow velocity waveforms, and velocimetric indices were calculated (resistive index, pulsatility index, and peak systolic velocity). Thereafter, 3-dimensional power Doppler sonography was used to assess vascularization of highly suggestive areas (gross papillary projections, solid areas, and thick septations), meaning a focused assessment ("sampling") of a suggestive area of the tumor. With a virtual organ computer-aided analysis program, vascular indices (vascularization index, flow index, and vascular flow index) were automatically calculated. A definitive histologic diagnosis was obtained in each case. RESULTS: Forty masses (82%) were malignant and 9 (18%) were benign. Morphologic evaluation revealed 10 (20%) unilocular solid masses, 20 (41%) multilocular solid masses, and 19 (39%) mostly solid masses. Blood flow was found in all cases. Median vascularization index (15.5% versus 8.2%; P = .002), flow index (33.6 versus 20.8; P = .007), and vascular flow index (5.2 versus 2.3; P = .001) were significantly higher in malignant tumors. No differences were found in resistive index (0.43 versus 0.45; P = .770), pulsatility index (0.62 versus 0.65; P = .694), and peak systolic velocity (15.6 versus 12 cm/s; P = .162). CONCLUSIONS: Three-dimensional power Doppler vascular sampling seems to be a promising tool for predicting ovarian cancer in vascularized complex adnexal masses. It could be better than conventional color pulsed Doppler imaging.

Adnexa Uteri↗
PubMed2001

Reconciling animal and human data in a cancer risk assessment of acrylonitrile.

OBJECTIVES: Bioassays of rats exposed to acrylonitrile have consistently detected an elevated incidence of central nervous system (CNS) cancer. In contrast, epidemiologic studies have not found a statistically stable increase in CNS cancer mortality. The purpose of this paper is to examine whether or not CNS cancers predicted from the most appropriate inhalation bioassay in rats are consistent with CNS cancers observed in 3 recent, large epidemiologic studies. METHODS: A linearized multistage model was fit to dose-response data from a rat inhalation bioassay to estimate carcinogenic potency. This potency was applied to epidemiologic studies of acrylonitrile-exposed workers. After adjustment for less than complete lifetime follow-up in the epidemiologic studies, consistency was examined between CNS cancers predicted by the model fit to the animal data for the exposure levels and sample sizes of the epidemiologicy studies and the CNS cancers observed in the epidemiologic studies. RESULTS: The model predicted totals of 17.7, 3.6, and 7.6 CNS cancer deaths for the studies. These predictions were not far from the observed CNS cancer deaths (12, 6, and 6) and were well within their 95% confidence intervals of 6.9-22.3, 2.2-13.1, and 2.2-13.1, respectively. CONCLUSIONS: The CNS cancer potency estimated from the best available inhalation bioassay was consistent with the observed deaths in the epidemiologic studies as long as continuous lifetime exposure was chosen as the exposure metric. The lack of observed excess in CNS cancer among the studied workers may have been due to low exposures, insufficient follow-up times, or both.

Acrylonitrile↗
PubMed2004

Tumor length and location of cancer on biopsy predict for side specific extraprostatic cancer extension.

PURPOSE: We studied preoperative variables in a contemporary series of men who underwent nonnerve sparing radical prostatectomy in an effort to establish criteria that would predict side specific extraprostatic extension (EPE) of cancer. MATERIALS AND METHODS: We reviewed the records of 430 patients who underwent radical prostatectomy for localized prostate cancer with no prior therapy between 1996 and 1998, and for whom we had at least sextant biopsy information. We evaluated biopsy data (Gleason score, maximum length of cancer in positive cores, percent of cancer per involved core, proportion of positive biopsy cores, tumor location and number of positive biopsy cores) and correlated these findings with EPE at the neurovascular bundle and posterior lateral (NVB/PL) region. RESULTS: We found that a higher number of positive cores, a higher biopsy Gleason score on a side, a positive core at the basal region, 50% or greater tumor in the core or a maximum tumor length of 7 mm or greater increased the likelihood that EPE was present at the NVB/PL region on the corresponding side of the prostate. On multivariate analysis maximum tumor length 7 mm or greater and positive basal core location were the strongest independent predictors of EPE at the NVB/PL region on a given side (p <0.0001 and 0.002, respectively). CONCLUSIONS: Excluding any patient with 1 positive biopsy core with a maximum tumor length of 7 mm or greater plus a positive basal core of any tumor length and grade can decrease the risk of EPE at the NVB/PL region to approximately 10%.

Biopsy↗
PubMed2006

The two-week wait cancer initiative on oral cancer; the predictive value of urgent referrals to an oral medicine unit.

BACKGROUND: The two-week wait cancer initiative was designed to speed up referral of patients suspected of having cancer. The National Institute of Clinical Excellence (NICE) has issued guidelines for head and neck cancers warranting urgent referral. OBJECTIVE: To look at the appropriate use of the two-week wait/urgent referrals by measuring the proportion of urgent referrals found to have cancer, to assess the sensitivity of the clinical guidelines and to explore how practitioners used them in primary care. METHOD: Collection and analysis of urgent referral letters and the clinic outcome for urgently referred cases over a one-year period in an oral medicine department. Screening of the biopsy service database to reveal any routine referrals subsequently found to have cancer. RESULTS: None of the routine referrals but eight percent of all urgent patients were found to have cancer, equating to 24% of the group in which malignancy was suspected. The predictive value of referring a case as suspected of oral cancer/with cancer symptoms was low, estimated at 7.9%. CONCLUSION: The referral guidelines on oral cancer symptoms developed by NICE may need further revision. Moreover, development of other appropriate adjuncts that aid visual inspection for the detection of oral cancer may improve the sensitivity of positive detections in primary care.

Adult↗
PubMed2005

Mammographic breast density and the Gail model for breast cancer risk prediction in a screening population.

BACKGROUND: Estimating an individual woman's absolute risk for breast cancer is essential for decision making about screening and preventive recommendations. Although the current standard, the Gail model, is well calibrated in populations, it performs poorly for individuals. Mammographic breast density (BD) may improve the predictive accuracy of the Gail model. METHODS: Prospective observational cohort of 81,777 women in the San Francisco Mammography Registry presenting for mammography during 1993 through 2002 who had no prior diagnosis of breast cancer. Breast density was rated by clinical radiologists using the Breast Imaging Reporting and Data System classification (almost entirely fat; scattered fibroglandular densities; heterogeneously dense; extremely dense). Breast cancer cases were identified through linkage to Northern California Surveillance Epidemiology End Results (SEER) program. We compared the predictive accuracy of models with Gail risk, breast density, and the combination. All models were adjusted for age and ethnicity. RESULTS: During 5.1 years of follow-up, 955 women were diagnosed with invasive breast cancer. The Gail model had modest predictive accuracy (concordance index (c-index) 0.67; 95% CI 0.65-0.68). Adding breast density to the model increased the predictive accuracy to 0.68 (95% CI .66-.70, p < 0.01 compared with the Gail model alone). The model containing only breast density adjusted for age and ethnicity had predictive accuracy equivalent to the Gail model (c-index 0.67, 95% CI 0.65-0.68). CONCLUSION: The addition of breast density measured by BI-RADS categories minimally improved the predictive accuracy of the Gail model. A model based on breast density alone adjusted for age and ethnicity was as accurate as the Gail model.

Adult↗
PubMed2006

Validation of a model of lung cancer risk prediction among smokers.

The Bach model was developed to predict the absolute 10-year risk of developing lung cancer among smokers by use of participants in the Carotene and Retinol Efficacy Trial of lung cancer prevention. We assessed the validity of the Bach model among 6239 smokers from the placebo arm of the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. The expected numbers of lung cancer cases and deaths without lung cancer were calculated from the Bach model and compared with the observed numbers of corresponding events over 10 years. We found that the risk model slightly underestimated the observed lung cancer risk (number of lung cancers expected/number observed = 0.89, 95% confidence interval [CI] = 0.80 to 0.99) over 10 years. The competing risk portion of the model substantially underestimated risk of non-lung cancer mortality (number of non-lung cancer deaths expected/number observed = 0.61, 95% CI = 0.57 to 0.64) over 10 years. The age-specific concordance indices for 10-year predictions were 0.77 (95% CI = 0.70 to 0.84), 0.59 (95% CI = 0.53 to 0.65), 0.62 (95% CI = 0.57 to 0.67), and 0.57 (95% CI = 0.49 to 0.67) for the age groups 50-54, 55-59, 60-64, and 65-69 years, respectively. Periodic radiographic screening in the ATBC Study may explain why slightly more cancers were observed than expected from the Bach model.

Age Distribution↗
PubMed2004

Predicting prostate cancer behavior using transcript profiles.

PURPOSE: Prostate cancer represents a disease with diverse clinical outcomes. Treatment strategies that optimize benefit and minimize morbidities depend on accurate estimates of disease status and likelihood of progression. Emerging technologies capable of qualitatively and quantitatively profiling genes expressed by neoplastic tissues may provide insights into tumor behavior. This review discusses the use of microarray based transcript expression profiling to stratify human cancers into risk categories. MATERIALS AND METHODS: MEDLINE was used to perform a comprehensive literature review of reports describing the assessment of gene expression profiles in malignant diseases. Particular emphasis was placed on studies developing models using individual genes or gene cohorts as predictors of prostate cancer outcome. RESULTS: Alterations in the expression of individual genes identified by microarray analyses have been used in studies of outcome in cancers of the prostate and other tissue types. Profiles of expressed genes have been used to develop prediction models that stratify cancers into prognostic categories based on relapse rates or responses to therapy. CONCLUSIONS: Gene expression profiles offer an opportunity for acquiring molecular determinants correlating with clinical outcome. With rare exceptions these profiles have yet to be validated or used in prospective studies. Future research will benefit from assessments of intratumor heterogeneity and host factors such as the immune response and hormonal milieu. The prospective validation of predictive models will serve to prove usefulness in the clinical arena.

Gene Expression Profiling↗
PubMed2004

The ratio of thymidine phosphorylase to dihydropyrimidine dehydrogenase in tumour tissues of patients with metastatic gastric cancer is predictive of the clinical response to 5'-deoxy-5-fluorouridine.

The aim of this work was to determine whether intratumour contents of thymidine phosphorylase (TP), which converts 5'-deoxy-5-fluorouridine (5'-DFUR) to 5-fluorouracil, and dihydropyrimidine dehydrogenase (DPD), which degrades 5-fluorouracil to inactive molecules, could be useful in predicting the response of patients with metastatic gastric cancer to chemotherapy using 5'-DFUR. Endoscopic biopsy specimens for the measurement of TP and DPD were obtained from the primary lesions before the start of combination chemotherapy, in which 5'-DFUR, cisplatin and mitomycin C were administered. TP and DPD were measured by enzyme-linked immunosorbent assays after the objective responses to chemotherapy had been confirmed. Twenty five patients were enrolled in this study and data for 22 patients in whom responses were confirmed were analysed. The median levels (ranges) of TP and DPD were 80 (4.9-360) and 44 (15-82) U/mg protein, respectively. The median value (range) of TP to DPD ratios was 1.9 (0.25-5.1). Eight patients with a complete or partial response to chemotherapy had significantly higher TP to DPD ratios than did the remaining patients with stable or progressive disease (P = 0.014). When a cut-off level of TP to DPD ratio was defined as the median value, the high-ratio group (n = 11) showed a significantly higher response rate (64% vs. 9.1%, P = 0.024) than the low-ratio group (n = 11). Overall survival of the high-ratio group was significantly longer than that of the low-ratio group (the median survival time; 300 days vs. 183 days, P = 0.047). The efficacy of 5'-DFUR could be optimised by preselecting patients with high TP/ DPD ratios in their tumour tissues, and this would be applicable to the treatment with capecitabine.

Adult↗
PubMed2005

Ability of 2 pretreatment risk assessment methods to predict prostate cancer recurrence after radical prostatectomy: data from CaPSURE.

PURPOSE: Two methods widely used to predict the risk of treatment failure after radical prostatectomy for localized prostate cancer are the 3 level D'Amico risk classification and the Kattan nomogram. Although they have been previously validated, to our knowledge they have not been compared in a community based cohort. We tested the 2 instruments in the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) database, a national registry of patients with prostate cancer, to assess their accuracy in a community based cohort. MATERIALS AND METHODS: Men were invited to join CaPSURE from 33 American urology practices, of which 30 were community based. A total of 1,701 men with localized prostate cancer (T1-3a) were treated with radical prostatectomy between 1989 and 2000. Patients who received neoadjuvant or adjuvant therapy were excluded. Recurrence was defined as 2 or more consecutive prostate specific antigen measurements of 0.2 ng/ml or greater, or a second treatment greater than 6 months after surgery. Freedom from progression (FFP) was based on life table estimates and Kaplan-Meier curves. Risk groups were compared using a Cox proportional hazards model and ANOVA. RESULTS: Based on the D'Amico classification 671 cases (39%) were classified as low risk, 446 (26%) were intermediate risk and 584 (34%) were high risk. Five-year FFP was 78%, 63% and 60% in the low, intermediate and high risk groups (HR 1.00, 1.87 and 2.32 respectively, p <0.0001). Mean 5-year FFP predicted by the Kattan nomogram in the same risk groups was 91%, 74% and 69%, respectively. Outcomes in the low risk group were tightly grouped about the mean but there was considerable dispersion of outcomes in the intermediate (30% to 98% FFP) and high (17% to 98%) risk groups. CONCLUSIONS: Stratifying patients in CaPSURE into low, intermediate and high risk categories for disease as described by D'Amico or applying the Kattan nomogram resulted in statistically significant differences in predicted 5-year FFP. However, there was considerable overlap of outcomes between the intermediate and high risk groups. This analysis suggests that simply estimating disease recurrence by stratifying patients into low, intermediate and high risk groups may not provide sufficient information for predicting outcomes among individuals.

Adult↗
PubMedDate not supplied

Progression-free interval in ovarian cancer and predictive value of an ex vivo chemoresponse assay.

The study objective was to determine the effectiveness of a phenotypic chemoresponse assay in predicting response to chemotherapy measured by progression-free interval (PFI) in a retrospective series of ovarian cancer patients whose tumor specimens had been tested with the ChemoFx assay. A statistically significant correlation between assay prediction of response and PFI was observed in 256 cases with an exact or partial match between drug(s) assayed and received. In 135 cases with an exact match, the hazard ratio for progression of the resistant group was 2.9 (confidence interval [CI]: 1.4-6.3; P < 0.01) compared to the sensitive group and 1.7 (CI: 1.2-2.5) for the intermediate compared to the sensitive group. The median PFI for patients treated with drugs assayed as resistant was 9 months, 14 months for those with drugs assayed as intermediately sensitive, and PFI had not been achieved for those with drugs assayed as sensitive. These data indicate that the ChemoFx assay is predictive of PFI in ovarian cancer. As the majority of ovarian cancers display different degrees of response to different chemotherapy agents ex vivo, the incorporation of assay information into treatment selection has the potential to improve clinical outcomes in ovarian cancer patients.

Adult↗
PubMed2006

Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience.

PURPOSE: To retrospectively determine whether a Bayesian network (BN) computer model can accurately predict the probability of breast cancer on the basis of risk factors and mammographic appearance of microcalcifications, to improve the positive predictive value (PPV) of biopsy, with pathologic examination and follow-up as reference standards. MATERIALS AND METHODS: The institutional review board approved this HIPAA-compliant study; informed consent was not required. Results of 111 consecutive image-guided breast biopsies performed for microcalcifications deemed suspicious by radiologists were analyzed. Mammograms obtained before biopsy were analyzed in a blinded manner by a breast imager who recorded Breast Imaging Reporting and Data System (BI-RADS) descriptors and provided a probability of malignancy. The BN uses probabilistic relationships between breast disease and mammography findings to estimate the risk of malignancy. Probability estimates from the radiologist and the BN were used to create receiver operating characteristic (ROC) curves, and area under the ROC curve (A(z)) values were compared. PPV of biopsy was also evaluated on the basis of these probability estimates. RESULTS: The BN and the radiologist achieved A(z) values of 0.919 and 0.916, respectively, which were not significantly different. If the 34 patients estimated by the BN to have less than a 10% probability of malignancy had not undergone biopsy, the PPV of biopsy would have increased from 21.6% to 31.2% without missing a breast cancer (P < .001). At this level, the radiologist's probability estimation improved the PPV to 30.0% (P < .001). CONCLUSION: A probabilistic model that includes BI-RADS descriptors for microcalcifications can distinguish between benign and malignant abnormalities at mammography as well as a breast imaging specialist can and may be able to improve the PPV of image-guided breast biopsy.

Adult↗
PubMed2001

Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention.

BACKGROUND: Women and their clinicians are increasingly encouraged to use risk estimates derived from statistical models, primarily that of Gail et al., to aid decision making regarding potential prevention options for breast cancer, including chemoprevention with tamoxifen. METHODS: We evaluated both the goodness of fit of the Gail et al. model 2 that predicts the risk of developing invasive breast cancer specifically and its discriminatory accuracy at the individual level in the Nurses' Health Study. We began with a cohort of 82 109 white women aged 45-71 years in 1992 and applied the model of Gail et al. to these women over a 5-year follow-up period to estimate a 5-year risk of invasive breast cancer. All statistical tests were two-sided. RESULTS: The model fit well in the total sample (ratio of expected [E] to observed [O] numbers of cases = 0.94; 95% confidence interval [CI] = 0.89 to 0.99). Underprediction was slightly greater for younger women (<60 years), but in most age and risk factor strata, E/O ratios were close to 1.0. The model fit equally well (E/O ratio = 0.93; 95% CI = 0.87 to 0.99) in a subset of women reporting recent screening (i.e., within 1 year before the baseline); among women with an estimated 5-year risk of developing invasive breast cancer of 1.67% or greater, the E/O ratio was 1.04 (95% CI = 0.96 to 1.12). The concordance statistic, which indicates discriminatory accuracy, for the Gail et al. model 2 when used to estimate 5-year risk was 0.58 (95% CI = 0.56 to 0.60). Only 3.3% of the 1354 cases of breast cancer observed in the cohort arose among women who fell into age-risk strata expected to have statistically significant net health benefits from prophylactic tamoxifen use. CONCLUSIONS: The Gail et al. model 2 fit well in this sample in terms of predicting numbers of breast cancer cases in specific risk factor strata but had modest discriminatory accuracy at the individual level. This finding has implications for use of the model in clinical counseling of individual women.

Aged↗
PubMed2001

Measurement of the systemic inflammatory response predicts cancer-specific and non-cancer survival in patients with cancer.

The assessment of prognosis in patients with advanced cancer remains problematical. The value of C-reactive protein concentration in this context has not been clearly defined. Patients with a diagnosis of colorectal (n = 182), gastric (n = 87), breast (n = 99), or bronchogenic (n = 404) cancer and who had measurements of C-reactive protein and albumin were identified. Median survival, from the time of sampling, ranged from 478 days in the colorectal cancer patients to 60 days in patients with bronchogenic cancer. On univariate analysis, there was, in each tumor type, a significant relationship between the duration of survival and both log10 C-reactive protein and albumin concentrations (P < or = 0.0002). On multivariate analysis, in each tumor type, log10 C-reactive protein remained a significant independent predictor of survival (P < or = 0.0002). When all four groups of cancer patients were analyzed (n = 772), the hazard ratio for a 10-fold increase in C-reactive protein concentration in cancer-specific survival was 2.21 (95% confidence interval = 1.92-2.56, P < 0.0001) and the corresponding hazard ratio for non-cancer survival was 5.48 (95% confidence interval = 3.55-8.46, P < 0.0001). The results of the present study indicate that in advanced cancer patients the presence of a systemic inflammatory response and the magnitude of that response predict the duration of cancer-specific and non-cancer survival.

Adult↗
PubMed2004

Preoperative neural network using combined magnetic resonance imaging variables, prostate specific antigen, and Gleason score to predict prostate cancer recurrence after radical prostatectomy.

OBJECTIVE: An artificial neural network analysis (ANNA) was developed to predict the biochemical recurrence more effectively than regression models based on the combined use of pelvic coil magnetic resonance imaging (pMRI), prostate specific antigen (PSA) and biopsy Gleason score in patients with clinically organ-confined prostate cancer after radical prostatectomy (RP). METHODS: Two-hundred-and-ten patients undergoing retropubic RP with pelvic lymphadenectomy were evaluated. Predictive study variables included clinical TNM classification, preoperative serum PSA, biopsy Gleason score, transrectal ultrasound (TRUS) findings, and pMRI findings. The predicted result was a biochemical failure (PSA >or=0.1 ng/ml). Using a five-way cross-validation method, the predicted ability of ANNA for a validation set of 200 randomly selected patients was compared with those of Cox regression analysis and "Kattan nomogram" by area under the receiver operating characteristic curve (AUC) analysis. RESULTS: Seventy-three patients (35%) failed at median follow-up of 61 (mean: 60, range: 2-94) months. Using similar input variables, the AUC of ANNA (0.765, 95% Confidence Interval [CI]: 0.704-0.825) was comparable (p > 0.05) to those for Cox regression (0.738, 95%CI: 0.691-0.819) and Kattan nomogram (0.728, 95%CI: 0.644-0.819). Contrarily, adding the pMRI findings, the ANNA is significantly (p < 0.05) superior to any other predictive model (0.897, 95%CI: 0.841-0.977). The Gleason score represented the most influential predictor (relative weight: 2.4) of PSA recurrence, followed by pMRI (2.2), and PSA (2.0). CONCLUSION: ANNA is superior to regression models to predict accurately biochemical recurrence. The relative importance of pMRI and the utility of ANNA to predict the PSA failure in patients referred for RP must be confirmed in further trials.

Biomarkers, Tumor↗
PubMed2004

Can patients' likelihood of benefiting from primary chemotherapy for breast cancer be predicted before commencement of treatment?

PURPOSE: Primary chemotherapy is commonly used in patients with breast cancer to downstage the primary tumour prior to surgery. There is a need to establish, prior to commencement of chemotherapy, predictors of clinical and pathological response, which may then be surrogate markers for patient survival and thus allow identification of patients who are most likely to benefit from such treatment. PATIENTS AND METHODS: A total of 104 patients with large and locally advanced breast cancers received an anthracycline/docetaxel-based regimen prior to surgery. Immunohistochemistry was carried out on pre-treatment core biopsies of the tumour to detect hormone receptors (oestrogen-ER; progesterone-PR), a proliferation marker (MIB-1), the oncoprotein Bcl-2, an extracellular matrix degradation enzyme (cathepsin D), p53, and an oestrogen associated protein (pS2). Both clinical and pathological response were assessed following completion of chemotherapy. RESULTS: Patients whose tumours did not express oestrogen receptor (p = 0.02) or did not express Bcl-2 (p < 0.01) had a better pathological response in a univariate analysis. However, in a multivariate model, it was only the absence of detectable Bcl-2 protein that predicted a better pathological response (p = 0.001). CONCLUSIONS: This study has identified that patients whose breast cancers are most likely to experience the greatest degree of tumour destruction by primary chemotherapy do not express either oestrogen receptors or Bcl-2. This may have important implications in the selection of patients with breast cancer for primary chemotherapy who are most likely to gain a survival benefit.

Adult↗
PubMedDate not supplied

Sialyl Lewis X expression in vascular permeating lesions as a factor for predicting colorectal cancer metastasis.

BACKGROUND/AIMS: To evaluate the potential of sialyl Lewis X (SLX) expression for predicting residual liver recurrence, we examined the vascular permeating lesions surrounding the metastatic liver tumors for SLX as a marker of residual liver recurrence. METHODOLOGY: Twenty-eight cases of metastatic liver tumors of colorectal cancers were examined using SLX monoclonal antibody for SLX expression in surrounding vascular permeating lesions. RESULTS: The cumulative residual liver recurrence rate in cases positive for SLX (SLX(+)) expression in the vascular permeating lesions surrounding the metastatic liver tumor was significantly higher than in the negative cases (p < 0.05). Furthermore, logistic regression analysis revealed that SLX positivity in the lesions surrounding the metastatic liver tumor was an important discriminant for residual liver recurrence (p = 0.0197). CONCLUSIONS: These results indicated that SLX expression in vascular permeating lesions surrounding the metastatic liver tumor is a predictive factor for residual liver recurrence.

Biomarkers, Tumor↗
PubMed1999

Immunohistochemical quantitation of thymidylate synthase expression in colorectal cancer metastases predicts for clinical outcome to fluorouracil-based chemotherapy.

PURPOSE: To determine whether immunohistochemical thymidylate synthase (TS) quantitation predicts for clinical outcome in patients with advanced colorectal cancer treated by fluorouracil (FUra)-based chemotherapy. PATIENTS AND METHODS: TS levels were measured immunohistochemically on archival specimens of colorectal cancer metastases from 48 patients homogenously treated by bolus FUra plus methotrexate alternating with continuous-infusion FUra plus leucovorin. These measurements were retrospectively correlated with patient characteristics and clinical outcome. RESULTS: A significant correlation was found between intratumoral TS expression and all the parameters of clinical outcome analyzed. In patients whose tumors had low (n = 27) and high (n = 21) TS levels, the overall response rates were 67% and 24%, respectively (P =.003). The percentage of tumor shrinkage after chemotherapy was linearly related to TS immunoreactivity (r =.56, P =.00004), and its mean values were 65% and 14% with low and high TS levels, respectively (P =.0001). By logistic regression analysis, low TS expression was the single best predictor of response to chemotherapy (relative probability, 5.0). In patients with low and high TS expression, the median time to progression was 9.6 months v 6.2 months (P =.005) and the median survival time 18.4 months v 15.4 months (P =.02), respectively. Two- and 3-year survival rates were 41% v 15% and 19% v 0% (P =.02), respectively. CONCLUSION: In this cohort of homogenously treated patients, intratumor TS content was a major predictor of clinical outcome. Immunohistochemical TS quantitation provides a convenient, low-cost technique for identifying patients unresponsive to TS inhibitors who may be candidates for alternative chemotherapy regimens.

Adult↗
PubMed2026

Quantifying uncertainty of predictions from cancer progression models.

MOTIVATION: Cancer progresses through the accumulation of genomic events. Cancer progression models such as Mutual Hazard Networks (MHNs) describe this dynamic, enabling prediction of temporal event positions and patient-specific risks of acquiring mutations. However, current MHN analyses rely on single most likely models and do not quantify the uncertainty inherent to parameter estimation. Assessing forecast stability is essential before using them to anticipate treatment-relevant mutations, adapt targeted therapies, or prioritize monitoring of patients at elevated progression risk. RESULTS: We address a key prerequisite for the responsible clinical use of cancer progression models by making MHN-derived predictions uncertainty-aware. We present a Bayesian framework for MHN that uses Markov Chain Monte Carlo to sample from the posterior distributions of model parameters and derived predictions. For practical use we implemented the Random-Walk Metropolis, Metropolis-Adjusted Langevin Algorithm (MALA), and simplified manifold MALA samplers as part of the existing mhn Python package. Only MALA and smMALA were successful in sampling from MHN posteriors, with MALA performing best. While most MHN parameters and predictions showed low posterior variance, a small subset displayed greater variability across the posterior distribution. This differentiation cannot be obtained from a single most likely model, emphasizing the need for uncertainty quantification, especially in clinical contexts. As an illustrative example, posterior sampling identified a subgroup of STK11$-$, KRAS$+$ lung adenocarcinoma patients with a high predicted short-term risk-with low variance across posterior samples-to develop an STK11 mutation. This subgroup exhibited poorer survival under immunotherapy, resembling patterns observed in STK11+ patients. AVAILABILITY AND IMPLEMENTATION: Our implementation is part of version 1.2.0 of the mhn package (https://github.com/spang-lab/LearnMHN). All analyses including the code to produce all figures in this article can be found under https://github.com/huy29433/MCMC-sampling-for-MHN (https://doi.org/10.5281/zenodo.21160219).

Humans↗