CLLU1 expression has prognostic value in chronic lymphocytic leukemia after first-line therapy in younger patients and in those with mutated IGHV genes.

CLLU1, located at chromosome 12q22, encodes a transcript specific to chronic lymphocytic leukemia and has potential prognostic value. We assessed the value of CLLU1 expression in the LRF CLL4 randomized trial. Samples from 515 patients with chronic lymphocytic leukemia were collected immediately before the start of treatment. After RNA extraction and cDNA synthesis, CLLU1 expression was assessed by quantitative polymerase chain reaction. In total, 247 and 268 samples were identified as having low and high CLLU1 expression, respectively. The median follow-up was 88 months. High CLLU1 expression was significantly correlated with unmutated IGHV genes, ZAP-70 and CD38 positivity, and absence of 13q deletion (all r>0.2, P

The prognostic impact of clinical and molecular features in hairy cell leukaemia variant and splenic marginal zone lymphoma.

Hairy cell leukaemia variant (HCL-variant) and splenic marginal zone lymphoma (SMZL) are disorders with overlapping features. We investigated the prognostic impact in these disorders of clinical and molecular features including IGH VDJ rearrangements, IGHV gene usage and TP 53 mutations. Clinical and laboratory data were collected before therapy from 35 HCL-variant and 68 SMZL cases. End-points were the need for treatment and overall survival. 97% of HCL-variant and 77% of SMZL cases required treatment (P = 0·009). Survival at 5 years was significantly worse in HCL-variant [57% (95% confidence interval 38-73%)] compared with SMZL [84% (71-91%); Hazard Ratio 2·25 (1·20-4·25), P = 0·01]. In HCL-variant, adverse prognostic factors for survival were older age (P = 0·04), anaemia (P = 0·01) and TP 53 mutations (P = 0·02). In SMZL, splenomegaly, anaemia and IGHV genes with >98% homology to the germline predicted the need for treatment; older age, anaemia and IGHV unmutated genes (100% homology) predicted shorter survival. IGHV gene usage had no impact on clinical outcome in either disease. The combination of unfavourable factors allowed patients to be stratified into risk groups with significant differences in survival. Although HCL-variant and SMZL share some features, they have different outcomes, influenced by clinical and biological factors.

A compendium of myeloma-associated chromosomal copy number abnormalities and their prognostic value.

To obtain a comprehensive genomic profile of presenting multiple myeloma cases we performed high-resolution single nucleotide polymorphism mapping array analysis in 114 samples alongside 258 samples analyzed by U133 Plus 2.0 expression array (Affymetrix). We examined DNA copy number alterations and loss of heterozygosity (LOH) to define the spectrum of minimally deleted regions in which relevant genes of interest can be found. The most frequent deletions are located at 1p (30%), 6q (33%), 8p (25%), 12p (15%), 13q (59%), 14q (39%), 16q (35%), 17p (7%), 20 (12%), and 22 (18%). In addition, copy number-neutral LOH, or uniparental disomy, was also prevalent on 1q (8%), 16q (9%), and X (20%), and was associated with regions of gain and loss. Based on fluorescence in situ hybridization and expression quartile analysis, genes of prognostic importance were found to be located at 1p (FAF1, CDKN2C), 1q (ANP32E), and 17p (TP53). In addition, we identified common homozygously deleted genes that have functions relevant to myeloma biology. Taken together, these analyses indicate that the crucial pathways in myeloma pathogenesis include the nuclear factor-κB pathway, apoptosis, cell-cycle regulation, Wnt signaling, and histone modifications. This study was registered at http://isrctn.org as ISRCTN68454111.

Eosinophilia is a favourable prognostic marker in oral squamous cell carcinoma

Suusyöpä on yleisin pään ja kaulan alueen pahanlaatuisista kasvaimista. Niistä yli 90 % on levyepiteelikarsinoomia. Koska suusyöpäpotilaan viisivuotisennuste on vain noin 50 %, on jatkuva tarve löytää keinoja ennustamaan potilaan selviytymistä ja ohjaamaan hoitoa. Suun levyepiteelikarsinooman ympäristössä havaitaan säännöllisesti eosinofiilejä. Eosinofiili on ihmisen immuunijärjestelmän erikoistunut solu, joiden määrä lisääntyy sekä tulehdusreaktioissa että syöpien läheisyydessä. Toistaiseksi ei tiedetä, miten eosinofiilit liittyvät suun levyepiteelikarsinoomaan, mutta oletuksena on, että suusyöpään liittyvällä eosinofilialla, TATE (tumor-associated tissue eosinophilia), voisi olla vaikutusta suun levyepiteelikarsinoomapotilaan ennusteeseen. Tämän tutkimuksen tarkoituksena oli selvittää TATE:n ilmenemistä ja vaikutusta potilaan ennusteeseen suun levyepiteelikarsinoomassa. Lisäksi tutkimus käsittelee potilaan ennusteen kannalta optimaalista eosinofiilimäärän raja-arvoa, jota voitaisiin käyttää patologin työkaluna ennusteen arvioinnissa. Tutkimusaineisto koostui Turun yliopiston Suupatologian laitoksella vuosina 2002-2010 tutkituista 122 suuontelon ja huulen limakalvokoepalasta, jotka oli otettu diagnostisia tarkoituksia varten 99 potilaalta. Tutkimuksen potilaista 44 oli naisia ja 55 miehiä, ja heidän keski-ikänsä oli 65,3 vuotta. Seuranta-aika oli keskimäärin 40,7 kk. Kaksi tutkijaa analysoivat hematoksyliini-eosiinilla värjätyt näytteet suurentamalla ne 400-kertaisiksi valomikroskoopilla. Eosinofiilien määrä laskettiin yhteensä kuudelta edustavimmalta syövän ja strooman alueelta. TATE:n suhde potilaan kliinispatologisiin piirteisiin ja selviytymiseen selvitettiin Turun yliopistollisen keskussairaalan potilastiedoistoista ja analysoitiin tilastollisesti käyttämällä Fischerin testiä. Työllä oli Varsinais-Suomen sairaanhoitopiirin eettisen toimikunnan lupa (nro T10/2011, päätös O31/11). Levyepiteelikarsinooman kliininen kuva vaihteli haavaisen muutoksen ollessa yleisin. Yleisin sijainti levyepiteelikarsinoomalle oli kieli. TATE:a löydettiin 61,5 %:sta (78/122) levyepiteelikarsinoomanäytteitä. Mikäli TATE:a ei löydetty tai sen määrä oli korkea, oli potilaan selviytyminen tilastollisesti merkitsevästi parempi kuin potilailla, joilla TATE oli matala. Lisäanalyyseissä havaittiin, että potilaan ennuste oli tilastollisesti merkitsevästi huonompi, mikäli TATE:n raja-arvo oli vähemmän kuin neljä eosinofiiliä per tutkittu mikroskooppinäkymä (HPF). TATE on täten merkki suun levyepiteelikarsinoomapotilaan paremmasta ennusteesta erityisesti, kun havaitaan enemmän kuin neljä eosinofiiliä/HPF. Tutkimustulosten varmistamiseksi tarvitaan kuitenkin jatkossa laajempia tutkimuksia.

Validation and Characterization of the Novel, Putative Prognostic Biomarkers CHAC1 and NFE2L2 in Breast Cancer

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Mesenchymal chondrosarcoma: prognostic factors and outcome in 113 patients. A European Musculoskeletal Oncology Society study

BACKGROUND: Mesenchymal chondrosarcoma (MCS) is a distinct, very rare sarcoma with little evidence supporting treatment recommendations. PATIENTS AND METHODS: Specialist centres collaborated to report prognostic factors and outcome for 113 patients. RESULTS: Median age was 30 years (range: 11-80), male/female ratio 1.1. Primary sites were extremities (40%), trunk (47%) and head and neck (13%), 41 arising primarily in soft tissue. Seventeen patients had metastases at diagnosis. Mean follow-up was 14.9 years (range: 1-34), median overall survival (OS) 17 years (95% confidence interval (CI): 10.3-28.6). Ninety-five of 96 patients with localised disease underwent surgery, 54 additionally received combination chemotherapy. Sixty-five of 95 patients are alive and 45 progression-free (5 local recurrence, 34 distant metastases, 11 combined). Median progression-free survival (PFS) and OS were 7 (95% CI: 3.03-10.96) and 20 (95% CI: 12.63-27.36) years respectively. Chemotherapy administration in patients with localised disease was associated with reduced risk of recurrence (P=0.046; hazard ratio (HR)=0.482 95% CI: 0.213-0.996) and death (P=0.004; HR=0.445 95% CI: 0.256-0.774). Clear resection margins predicted less frequent local recurrence (2% versus 27%; P=0.002). Primary site and origin did not influence survival. The absence of metastases at diagnosis was associated with a significantly better outcome (P<0.0001). Data on radiotherapy indications, dose and fractionation were insufficiently complete, to allow comment of its impact on outcomes. Median OS for patients with metastases at presentation was 3 years (95% CI: 0-4.25). CONCLUSIONS: Prognosis in MCS varies considerably. Metastatic disease at diagnosis has the strongest impact on survival. Complete resection and adjuvant chemotherapy should be considered as standard of care for localised disease.

Chronic low back pain among French healthcare workers and prognostic factors of return to work (RTW): a non-randomized controlled trial

International audience

Contribution to the study of prognostic factors in canine oral squamous cell carcinoma

Tese de Doutoramento em Ciências Veterinárias, na Especialidade de Clínica

Predictors of in-hospital mortality among cardiogenic shock patients. Prognostic and therapeutic implications

Cardiogenic shock (CS) has a poor prognosis. The heterogeneity in the mortality through different subgroups suggests that some factors can be useful to perform risk stratification and guide management. We aimed to find predictors of in-hospital mortality in these patients. We analyzed all cases of cardiogenic shock due to medical conditions admitted in our intensive acute cardiovascular care unity from November 2010 till November 2015. Clinical, biochemical and hemodynamic variables were registered, as was the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) profile at 24 h of CS diagnosis. From a total of 281 patients, 28 died within the first 24 h and were not included in the analysis. A total of 253 patients survived the first 24 h, mean age was 68.8 ± 14.4 years, and 174 (68.8%) were men. Etiologies: acute coronary syndrome 146 (57.7%), acute heart failure 60 (23.7%), arrhythmias 35 (13.8%), and others 12 (4.8%). A total of 91 patients (36.0%) died during hospitalization. We found the following independent predictors of in-hospital mortality: age (odds ratio [OR] 1.032, 95% confidence interval [CI] 1.003–1.062), blood glucose (OR 1.004, 95% CI 1.001–1.008), heart rate (OR 1.014, 95% CI 1.001–1.028), and INTERMACS profile (OR 0.168, 95% CI 0.107–0.266). In patients with CS the INTERMACS profile at 24 h of diagnosis was associated with higher in-hospital mortality. This and other prognostic variables (age, blood glucose, and heart rate) may be useful for risk stratification and to select appropriate medical or invasive interventions.

A database ATP simulated waveforms of shunt reactor switching cases with vacuum breakers on motor circuits

This paper presents a database ATP (Alternative Transient Program) simulated waveforms for shunt reactor switching cases with vacuum breakers in motor circuits following interruption of the starting current. The targeted objective is to provide multiple reignition simulated data for diagnostic and prognostic algorithms development, but also to help ATP users with practical study cases and component data compilation for shunt reactor switching. This method can be easily applied with different data for the different dielectric curves of circuit-breakers and networks. This paper presents design details, discusses some of the available cases and the advantages of such simulated data.

Prognosis of bearing failure based on health state estimation

This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Central venous oxygen saturation monitoring

It has been established that mixed venous oxygen saturation (SvO2) reflects the balance between systemic oxygen deliver y and consumption. Literature indicates that it is a valuable clinical indicator and has good prognostic value early in patient course. This article aims to establish the usefulness of SvO2 as a clinical indicator. A secondary aim was to determine whether central venous oxygen saturation (ScvO2) and SvO2 are interchangeable. Of particular relevance to cardiac nurses is the link between decreased SvO2 and cardiac failure in patients with myocardial infarction, and with decline in myocardial function, clinical shock and arrhythmias. While absolute values ScvO2 and SvO2 are not interchangeable, ScvO2 and SvO2are equivalent in terms of clinical course. Additionally, ScvO2 monitoring is a safer and less costly alternative to SvO2 monitoring. It can be concluded that continuous ScvO2 monitoring should potentially be undertaken in patients at risk of haemodynamic instability.