Prognostic Estimates Research Articles

Criteria for Referral of Patients With Advanced Heart Failure for Specialized Palliative Care

BackgroundPatients with advanced heart failure have substantial supportive care needs. Specialist palliative care can be beneficial, but it is unclear who is most appropriate for referral and when patients should be referred. ObjectivesWe conducted a Delphi study of international experts to identify consensus referral criteria for specialist palliative care for patients with advanced heart failure. MethodsClinicians from 5 continents with expertise in the integration of cardiology and palliative care were asked to rate 34 disease-based, 24 needs-based, and 9 time-based criteria over 3 rounds. Consensus was defined a priori as ≥70% agreement. A criterion was coded as major if the experts endorsed that meeting that criterion alone was adequate to justify a referral. ResultsThe response rate was 44 of 46 (96%), 41 of 46 (89%), and 43 of 46 (93%) in the first, second, and third rounds, respectively. Panelists reached consensus on 25 major criteria for specialist palliative care referral. The 25 major criteria were categorized under 6 topics, including “advanced/refractory heart failure, comorbidities, and complications” (eg, cardiac cachexia, cardiorenal syndrome) (n = 8), “advanced heart failure therapies” (eg, chronic inotropes, precardiac transplant) (n = 4), “hospital utilization” (eg, emergency room visits, hospitalization) (n = 2), “prognostic estimate” (n = 1), “symptom burden/distress” (eg, severe physical/emotional/spiritual distress) (n = 6), and “decision making/social support” (eg, goals-of-care discussions) (n = 4). The majority (68%) of major criteria had ≥90% agreement. ConclusionsInternational experts reached consensus on a large number of criteria for referral to specialist palliative care. With further validation, these criteria may be useful for standardizing palliative care access in the inpatient and/or outpatient settings.

Impact of early tumor shrinkage on quality of life in patients treated with first-line cetuximab plus chemotherapy for unresectable metastatic colorectal cancer: results of Phase II QUACK trial

PurposeAlthough early tumor shrinkage (ETS) is a predictor of improved overall survival (OS), the association between ETS and health-related quality of life (HRQOL) remains unclear for patients with metastatic colorectal cancer (mCRC) treated with first-line cetuximab plus chemotherapy.MethodsThe data were collected from a prospective trial that assessed HRQOL using the EORTC QLQ-C30. The impact of ETS on HRQOL was estimated using a linear mixed-effects model for repeated measures.ResultsETS was achieved in 82 (64.1%) of 128 mCRC patients treated with first-line cetuximab plus chemotherapy, and these patients had a significantly longer OS than those without ETS (HR, 0.38; 95% CI, 0.20–0.72; P = .002). Asymptomatic patients with ETS had a favorable OS, while symptomatic patients without ETS had a worse OS (2-year OS rates, 77.8% vs. 42.5%). Symptomatic patients with ETS had similar outcomes as asymptomatic patients without ETS (2-year OS rates, 64.1% vs. 67.0%). For symptomatic patients, ETS was associated with improved HRQOL scores between baseline and 8 weeks: the mean changes for patients with and without ETS were 5.86 and -4.94 for global health status (GHS)/QOL, 26.73 and 3.79 for physical functioning, and 13.58 and -3.10 for social functioning, respectively. The improved HRQOL was comparable to that of asymptomatic patients without ETS. For asymptomatic patients, ETS showed a decreased deterioration in HRQOL.ConclusionOur findings highlight the importance of ETS for HRQOL and prognostic estimates, and assessing ETS may provide clinically useful information for physicians and patients to make more informed decisions.

Three-Dimensional Hindcast of Nitrogen and Phosphorus Biogeochemical Dynamics in Lake Onego Ecosystem, 1985–2015. Part I: Long-Term Dynamics and Spatial Distribution

Despite a wide-ranging research, there is almost no information regarding the major biogeochemical fluxes that could characterize the past and present state of the European Lake Onego ecosystem and be used for reliable prognostic estimates of its future. To enable such capacity, we adapted and implemented a three-dimensional coupled hydrodynamical biogeochemical model of the nutrient cycles in Lake Onego. The model was used to reconstruct three decades of Lake Onego ecosystem dynamics with daily resolution on a 2 × 2 km grid. A comparison with available information from Lake Onego and other large boreal lakes proves that this hindcast is plausible enough to be used as a form of reanalysis. This model will be used as a form of studies of Lake Onego ecosystem, including long-term projections of ecosystem evolution under different scenarios of climate change and socio-economic development.

Economic factors of increasing fertility in the Volga Federal District: a retrospective analysis (2000–2020)

Purpose: to determine the economic factors that steadily influenced reproductive trends in the Volga Federal District in 2000-2020, their regional differentiation. The hypothesis of the study: the dynamics of the birth rate is predetermined, among other things, by economic factors (of a general economic nature and economic activity of households). With a positive change in the economic well-being of the population and households, stable prerequisites are formed for the growth of the birth rate in the Volga Federal District.Methods: the correlation and regression analysis of the total fertility rate and economic predictors for 2000-2020 of the Volga Federal District regions was used. Econometric prerequisites for determining reproductive trends are formed based on changes in macro- and microeconomic indicators of the economic well-being of the region and individual households.Results: regional differences in the influence of economic factors on fertility are revealed: direct linear dependence on the volume of investments per capita and the level of employment; inverse dependence on the level of poverty and the share of household spending on food (except for the Republic of Bashkortostan). When assessing the inverse linear dependence on the indexation of prices for primary housing, the coefficient of determination is insufficient (except for the Udmurt Republic), as in the case of assessing the impact of the unemployment rate (the factor is insignificant for the Republic of Bashkortostan, Kirov Region, Perm Krai). The growth and decrease in monthly consumer spending lead to a decrease in the birth rate.Conclusions and Relevance: one-factor regression analysis showed that in the Volga Federal District, the formation of reproductive trends is negatively affected by an increase in the share of spending on essential goods. Multivariate regression analysis revealed a correlation of fertility rates with a steady increase in the level of employment. The presented approach can be used to describe the prerequisites for the formation of stable reproductive trends in other districts and regions of Russia for the implementation of preventive measures of the demographic policy of the state in order to maintain the stability and positive development of the demographic situation, prognostic estimates of trends of deviation from the positive trend.

Integrated Analysis of a Ferroptosis-Related LncRNA Signature for Evaluating the Prognosis of Patients with Colorectal Cancer.

LncRNAs have been well known for their multiple functions in the tumorigenesis, development, and relapse of colorectal cancer (CRC). Accumulating studies demonstrated that the expression of lncRNAs can be regulated by ferroptosis, a biological process that has been revealed to suppress CRC progression. However, the functions and clinical implications of ferroptosis-associated lncRNAs in CRC remain largely unknown. We, herein, aim to construct a prognostic signature with ferroptosis-related lncRNAs for the prognostic estimation of CRC patients. Firstly, we identified the lncRNAs related to ferroptosis based on the RNA-Seq data of CRC from the TCGA database. The univariate and multivariate Cox analyses were then performed to establish a prognostic signature composed of eight ferroptosis-related lncRNAs (AL161729.4, AC010973.2, CCDC144NL-AS1, AC009549.1, LINC01857, AP003555.1, AC099850.3, and AC008494.3). Furthermore, we divided the CRC patients into high- and low-risk groups based on the signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that in the low-risk group (p = 3.31 × 10−11). Moreover, the patients in the high-risk groups had shorter recurrence-free survival (RFS) (p = 6.5 × 10−3) and disease-free survival (DFS) (p = 4.27 × 10−4), as well as higher tumor recurrence rate. Additionally, we found that the oncogenic pathways were enriched in the high-risk group, whereas the ferroptosis pathway that probably repressed CRC development was enriched in the low-risk group. In summary, our signature may provide a theoretical foundation for not only accurate judgment for prognosis but also evaluation for recurrence and metastasis in CRC patients.

Definitive chemoradiotherapy +/- induction chemotherapy in esophageal cancer: A real-world experience.

e16072 Background: The SEER 5-year overall survival rate for all stages of esophageal cancer (EC) was 25% in 2019. Definitive chemoradiation (CRT) remains the primary treatment approach for locally advanced EC in the US, however, there are data to support use of induction chemotherapy (CT) in addition to CRT, particularly in adenocarcinoma (AC) histology. The purpose of our study was to assess outcomes in EC patients treated with definitive CRT (+/- induction) to determine which prognostic factors predicted for better survival in a recent, real-world cohort of patients, including those with limited stage IV disease. Methods: This retrospective study included Stages II-IVB (AJCC 8th ed.) EC patients treated with definitive CRT (radiation dose of ≥40 Gy and at least two cycles of concurrent CT [+/- induction CT, +/- esophagectomy]) at our institution between 2008 and 2020. To analyze prognostic factors and estimate OS, univariate models (UVA) and a multivariate (MVA) Cox proportional hazards regression model including age, Stage (II, III, IVA, IVB), AC vs. SCC, esophagectomy, ECOG performance status (PS), and induction CT were performed. Results: Of the 183 patients treated with definitive CRT, 18 were stage II, 119 stage III, 21 stage IVA, and 25 stage IVB. There were 45 SCC and 138 AC patients (Table). Prognostic factors associated with prolonged OS on MVA included lower PS (p<0.01) and esophagectomy (p = 0.05). Stage IVA was associated with shorter survival (p<0.01). Induction CT (delivered in 53% of AC, 31% SCC) was associated with improved survival on UVA (p=0.04), but not MVA (p = 0.08). By histology, 5-year survival rate was 42.7% and 18.2% for AC and SCC, respectively. Conclusions: At our institution, those who received an esophagectomy and those with lower ECOG scores had better survival. The 5-year survival rate was higher for AC patients compared to SCC, with more AC patients receiving esophagectomy and induction CT (significant on UVA, but not MVA). The 5-year survival rate for AC in our study was nearly identical to that seen in the CROSS trial (Shapiro et al. 2015) AC cohort but included >25% stage IV patients. This modern cohort also included poor PS (ECOG≥2) patients (9.2% AC and 13.6% SCC), suggesting induction CT, in addition to pre-operative CRT + surgery, may have added benefit in a real-world practice. Thus, further prospective study is needed.[Table: see text]

Understanding Prognosis: Discrepancy in Prognosis Estimates Between Patients With Cirrhosis and their Hepatologists

Patients require a clear understanding of their prognosis to make informed decisions about their care. The aim of this study was to compare the perceptions of prognosis and transplant candidacy between patients with cirrhosis and their hepatologists. Patients with cirrhosis and their hepatologists were prospectively recruited at an urban liver transplant center. Patients and hepatologists were asked about transplant candidacy and about how many years patients would live with and without a liver transplant. Agreement between patients and hepatologists was assessed with the weighted kappa statistic. Associations between patient/hepatologists' prognostic estimates and those predicted by patients' Model for End-Stage Liver Disease-Sodium (MELD-Na) score were estimated using the Pearson correlation coefficient. Seventy patients and 6 hepatologists were enrolled in the study. Patients were predominantly male (61.4%) and white (68.6%), with a mean MELD-Na score of 19 ± 9. There was no-slight agreement between patients and hepatologists regarding survival without and with a liver transplant (κ= 0.1 and 0.2, respectively), with patients more optimistic than their hepatologists. There was greater agreement between patients and hepatologists about transplant candidacy (κ= 0.6). There was a negligible association between MELD-Na and patient estimates (r= -0.24, P= .05) but a moderate association between MELD-Na and hepatologist estimates (r= -0.51, P < .001), with higher MELD-Na scores associated with lower predicted survival. Patients with cirrhosis are more optimistic and less accurate in their predictions of survival compared with hepatologists, although they are more realistic about their transplant candidacy. Aligning patient and provider expectations may increase the likelihood that patients receive value-concordant care.

An Advanced System for the Visualisation and Prediction of Equipment Ageing

The control of major hazards involving dangerous substances in the chemical and process industry requires verifying equipment ageing according to the current legislation. This means to monitor its real conditions regarding degradation mechanisms and forecast their evolution over time. A system, named Virtual Sensor, supports this activity that is usually conducted during on-field inspections (safety walks). It is designed to collect ageing-related information, process data through some models, and produce prognostic estimates regarding the corrosion rate, the probability of the critical pit, the corrosion evolution on the equipment surface, and the residual lifetime, visualising the results in Augmented Reality (AR). An atmospheric storage tank of diesel oil was chosen as the case study; its 3D model was realised, and a miniature model was reproduced in the laboratory. Through the Virtual Sensor, data of past inspections were acquired. The application successfully managed and elaborated these data, showing the outputs in AR during a safety walk.

Development and validation of an eight-gene signature based predictive model to evaluate the prognosis of hepatocellular carcinoma patients: a bioinformatic study.

BackgroundHepatocellular carcinoma (HCC) is a malignant tumor with a poor prognosis, however, biomarkers for the prognostic assessment of HCC remain suboptimal. Consequently, we aimed to develop a reliable tool for prognostic estimation of HCC.MethodsDifferentially expressed genes (DEGs) between HCC and adjacent normal tissues in 3 Gene Expression Omnibus (GEO) datasets were identified, followed by hub gene selection and least absolute shrinkage and selection operator (LASSO) Cox regression to develop a prognostic gene signature. Kaplan-Meier survival analysis, univariate and multivariate Cox regression, time-dependent area under the curve (AUC), and integrated value of time-dependent AUC (iAUC) were used to assess the relationship between predictors and clinical outcomes in the training and validation datasets. Then we built nomograms including gene signature and clinicopathological factors to forecast the probability of death. Moreover, we performed quantitative real-time PCR (qPCR) to compare the expression of prognostic genes between HCC and adjacent normal tissues. Finally, the relationship between prognostic genes and tumor microenvironment (TME) was investigated using immune cell infiltration algorithms and single cell transcriptomic database.ResultsEight prognostic genes (CDC20, PTTG1, TOP2A, CXCL2, CXCL14, CYP2C9, MT1F, and GHR) were finally identified to construct the gene signature. Each patient’s risk score was calculated according to the gene signature. Patients with high-risk scores showed worse outcomes in the training set [hazard ratio (HR) =3.404, P<0.001]. Risk score, age, body mass index (BMI), and TNM stage were identified as independent prognostic factors for overall survival (OS) in the training set. The nomogram including risk score and other independent prognostic factors showed better performance as opposed to the clinicopathological model. In the validation dataset, we obtained the similar results as well. Moreover, we found a close relationship between risk score and immune cell infiltration. Patients with high-risk scores had elevated expression of immune checkpoint genes, indicating that these patients may be more suitable for immunotherapy.ConclusionsWe have established and validated an eight-gene based prognostic model, which could be an effective tool for the prognostic evaluation of HCC patients.

Development of an Image Analysis-Based Prognosis Score Using Google's Teachable Machine in Melanoma.

Simple SummaryThe increase in adjuvant treatment of melanoma patients makes it necessary to provide the most accurate prognostic assessment possible, even at early stages of the disease. Although conventional risk stratification correctly identifies most patients in need of adjuvant treatment, there are some patients who, despite having a low tumor stage, have poor prognosis and could therefore benefit from early therapy. To close this gap in prognosis estimation, deep learning-based image analyses of histological sections could play a central role in the future. The aim of this study was to investigate whether such an analysis is possible only using basic image analysis of 831 H&E-stained melanoma sections using Google’s Teachable Machine. Although the classification obtained does not provide an additional prognostic estimate to conventional melanoma classification, this study shows that prognostic prediction is possible at the mere cellular image level.Background: The increasing number of melanoma patients makes it necessary to establish new strategies for prognosis assessment to ensure follow-up care. Deep-learning-based image analysis of primary melanoma could be a future component of risk stratification. Objectives: To develop a risk score for overall survival based on image analysis through artificial intelligence (AI) and validate it in a test cohort. Methods: Hematoxylin and eosin (H&E) stained sections of 831 melanomas, diagnosed from 2012–2015 were photographed and used to perform deep-learning-based group classification. For this purpose, the freely available software of Google’s teachable machine was used. Five hundred patient sections were used as the training cohort, and 331 sections served as the test cohort. Results: Using Google’s Teachable Machine, a prognosis score for overall survival could be developed that achieved a statistically significant prognosis estimate with an AUC of 0.694 in a ROC analysis based solely on image sections of approximately 250 × 250 µm. The prognosis group “low-risk” (n = 230) showed an overall survival rate of 93%, whereas the prognosis group “high-risk” (n = 101) showed an overall survival rate of 77.2%. Conclusions: The study supports the possibility of using deep learning-based classification systems for risk stratification in melanoma. The AI assessment used in this study provides a significant risk estimate in melanoma, but it does not considerably improve the existing risk classification based on the TNM classification.

Deletion of TRIB3 disrupts the tumor progression induced by integrin \u03b1v\u03b23 in lung cancer

BackgroundIntegrin αvβ3 has been proposed as crucial determinant for tumor sustained progression and a molecular marker for the estimation of tumor angiogenesis. Our study suggested that integrin αvβ3 could efficiently promote lung cancer cell proliferation and stem-like phenotypes in a tribbles homolog 3 (TRIB3) dependent manner.ResultIntegrin αvβ3 could mediate the activation of FAK/AKT pro-survival signaling pathway. Meanwhile, activated TRIB3 interacted with AKT to upregulated FOXO1 and SOX2 expression, resulting in sustained tumor progression in lung cancer. Our further analysis revealed that TRIB3 was significantly upregulated in lung tumor tissues and correlated with the poor outcome in clinical patients, indicating the potential role of TRIB3 in diagnostic and prognostic estimation for patients with lung cancer.ConclusionOur study showed here for the first time that integrin αvβ3 promote lung cancer development by activating the FAK/AKT/SOX2 axis in a TRIB3 dependent signaling pathway, and interrupting TRIB3/AKT interaction significantly improved the outcome of chemotherapy in tumor-bearing mice, representing a promising therapeutic strategy in lung cancer.

Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review.

BackgroundWith the accumulation of electronic health records and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of artificial intelligence based on electronic health records in cancer care.ObjectiveThe aim of this study was to conduct a review to introduce the current state and limitations of artificial intelligence based on electronic health records of patients with cancer and to summarize the performance of artificial intelligence in mining electronic health records and its impact on cancer care.MethodsThree databases were systematically searched to retrieve potentially relevant papers published from January 2009 to October 2020. Four principal reviewers assessed the quality of the papers and reviewed them for eligibility based on the inclusion criteria in the extracted data. The summary measures used in this analysis were the number and frequency of occurrence of the themes.ResultsOf the 1034 papers considered, 148 papers met the inclusion criteria. Cancer care, especially cancers of female organs and digestive organs, could benefit from artificial intelligence based on electronic health records through cancer emergencies and prognostic estimates, cancer diagnosis and prediction, tumor stage detection, cancer case detection, and treatment pattern recognition. The models can always achieve an area under the curve of 0.7. Ensemble methods and deep learning are on the rise. In addition, electronic medical records in the existing studies are mainly in English and from private institutional databases.ConclusionsArtificial intelligence based on electronic health records performed well and could be useful for cancer care. Improving the performance of artificial intelligence can help patients receive more scientific-based and accurate treatments. There is a need for the development of new methods and electronic health record data sharing and for increased passion and support from cancer specialists.

The accuracy of clinician predictions of survival in the Prognosis in Palliative care Study II (PiPS2): A prospective observational study.

BackgroundPrognostic information is important for patients with cancer, their families, and clinicians. In practice, survival predictions are made by clinicians based on their experience, judgement, and intuition. Previous studies have reported that clinicians’ survival predictions are often inaccurate. This study reports a secondary analysis of data from the Prognosis in Palliative care Study II (PiPS2) to assess the accuracy of survival estimates made by doctors and nurses.Methods and findingsAdult patients (n = 1833) with incurable, locally advanced or metastatic cancer, recently referred to palliative care services (community teams, hospital teams, and inpatient palliative care units) were recruited. Doctors (n = 431) and nurses (n = 777) provided independent prognostic predictions and an agreed multi-professional prediction for each patient. Clinicians provided prognostic estimates in several formats including predictions about length of survival and probability of surviving to certain time points. There was a minimum follow up of three months or until death (whichever was sooner; maximum follow-up 783 days).Agreed multi-professional predictions about whether patients would survive for days, weeks or months+ were accurate on 61.9% of occasions. The positive predictive value of clinicians’ predictions about imminent death (within one week) was 77% for doctors and 79% for nurses. The sensitivity of these predictions was low (37% and 35% respectively). Specific predictions about how many weeks patients would survive were not very accurate but showed good discrimination (patients estimated to survive for shorted periods had worse outcomes). The accuracy of clinicians’ probabilistic predictions (assessed using Brier’s scores) was consistently better than chance, improved with proximity to death and showed good discrimination between groups of patients with different survival outcomes.ConclusionsUsing a variety of different approaches, this study found that clinicians predictions of survival show good discrimination and accuracy, regardless of whether the predictions are about how long or how likely patients are to survive. Accuracy improves with proximity to death. Although the positive predictive value of estimates of imminent death are relatively high, the sensitivity of such predictions is relatively low. Despite limitations, the clinical prediction of survival should remain the benchmark against which any innovations in prognostication are judged.Study registrationISRCTN13688211. http://www.isrctn.com/ISRCTN13688211.

Acute but not chronic heart failure is associated with higher mortality among patients hospitalized with pneumonia: An analysis of a nationwide database

BackgroundAmong patients admitted for pneumonia, heart failure (HF) is associated with worse outcomes. It is unclear whether this association is due to acute HF exacerbations, complex medical management, or chronic co-morbid conditions. MethodsThis is a retrospective cohort study of patients admitted between July 2010 and June 2015 at 651 US hospitals with a principal diagnosis of either pneumonia or secondary diagnosis of pneumonia with a primary diagnosis of respiratory failure or sepsis. Comorbidities were identified by ICD-9 codes and medical management by daily charge codes. Patients were categorized according to the presence and acuity of admission diagnosis of HF. In-hospital mortality was the primary outcome. Secondary outcomes included length of stay, hospital cost, ICU admission, use of mechanical ventilation, vasopressors and inotropes. Logistic regression was used to study the association of outcomes with presence and acuity of HF. ResultsOf 783,702 patients who met inclusion criteria, 212,203 (27%) had a diagnosis of HF. Of these, 56,306 (26.5%) had acute while 48,188 (22.7%) had chronic HF on admission; 51% had a diagnosis of unspecified HF. In multivariable-adjusted models, having any HF was associated with increased mortality (OR 1.35 [1.33 - 1.38]) compared to those without HF; increased mortality was associated with acute HF (OR 1.19 [1.15 - 1.22]) but not chronic HF (OR 0.92 [0.89 - 0.96]). ConclusionThe worse outcomes for pneumonia patients with HF appear due to acute HF exacerbations. Adjustment for HF without accounting for chronicity could lead to biased prognostic and billing estimates.

Association of the careggi collateral score with radiological outcomes after thrombectomy for stroke with an occlusion of the middle cerebral artery.

We aimed to examine the association between Careggi Collateral Score (CCS) and radiological outcomes in a large multicenter cohort of patients receiving thrombectomy for stroke with occlusion of middle cerebral artery (MCA). We conducted a study on prospectively collected data from 1785 patients enrolled in the Italian Registry of Endovascular Treatment in Acute Stroke. According to the extension of the retrograde reperfusion in the cortical anterior cerebral artery-MCA territories, CCS ranges from 0 (absence of retrograde filling) to 4 (visualization of collaterals until the alar segment of the MCA). Radiological outcomes at 24h were the presence and severity of infarct growth defined by the absolute change in ASPECTS from baseline to 24h; presence and severity of cerebral bleeding defined as no ICH, HI-1, HI-2, PH-1, or PH-2; presence and severity of cerebral edema (CED) defined as no CED, CED-1, CED-2, or CED-3. Using CCS = 0 as reference, ORs of CCS grades were significantly associated in the direction of better radiological outcome on infarct growth (0.517 for CCS = 1, 0.413 for CCS = 2, 0.358 for CCS = 3, 0.236 for CCS = 4), cerebral bleeding grading (0.485 for CCS = 1, 0.445 for CCS = 2, 0.400 for CCS = 3, 0.379 for CCS = 4), and CED grading (0.734 for CCS = 1, 0.301 for CCS = 2, 0.295 for CCS = 3, 0.255 for CSS = 4) shift in ordinal regression analysis after adjustment for pre-defined variables (age, NIHSS score, ASPECTS, occlusion site, onset-to-groin puncture time, procedure time, and TICI score). Using CCS = 4 as reference, ORs of CCS grades were significantly associated in the direction of worse radiological outcome on infarct growth (1.521 for CCS = 3, 1.754 for CCS = 2, 2.193 for CCS = 1, 4.244 for CCS = 0), cerebral bleeding grading (2.498 for CCS = 0), and CED grading (1.365 for CCS = 2, 2.876 for CCS = 1, 3.916 for CCS = 0) shift. The CCS could improve the prognostic estimate of radiological outcomes in patients receiving thrombectomy for stroke with MCA occlusion.

СТАТИСТИЧЕСКОЕ ПРОГНОЗИРОВАНИЕ НАКОПЛЕНИЯ 137Cs В ПРОДУКЦИИ РАСТЕНИЕВОДСТВА НА РАДИОАКТИВНО ЗАГРЯЗНЕННЫХ ТЕРРИТОРИЯХ

Purpose: the development of statistical models for forecasting the accumulation of 137Cs in crop production, model parameterisation and prognostic estimates for the territories of the Bryansk region contaminated with 137Cs because of the Chernobyl accident. Material and methods: The use of a probabilistic approach for correct predictive assessments of the safety of agricultural products from radioactively contaminated agricultural lands has been substantiated. Analytical models were developed in the framework of a probabilistic approach to predict the risks of radioactive contamination of crop products, to assess the permissible levels of contamination of arable lands and the time of their natural remediation. Results: Based on a statistical analysis of radioecological survey data, it was established that the 137Cs contamination density of the soil follows a lognormal distribution law with a high level of significance. For farms in the south-western districts of the Bryansk region, it was shown that, if the average values of 137Cs content in crop production corresponded to the established standard, the risks of its excess could reach 30 %. This is due to the variability of 137Cs soil contamination densities and migration parameters. The dependences of limiting soil contamination densities of 137Cs on the risk of exceeding the standards (RES) of the content of this radionuclide in products were presented. The time of natural rehabilitation of arable agricultural land with a given risk for products of 10 % can exceed 30 years. Conclusion: The application of probabilistic methods to predict the consequences of 137Cs contamination of agricultural lands makes it possible to correct practical recommendations developed on the basis of a deterministic approach. The results of prognostic calculations are the basis for planning and evaluating the possibility of returning territories contaminated by 137Cs to economic use. The developed methodology and models can be used in the development of decision support systems for the remediation of agricultural lands exposed to radioactive fallout.

Effect of additional cytogenetic abnormalities on survival in arsenic trioxide-treated acute promyelocytic leukemia

AbstractFrontline arsenic trioxide (ATO)–based treatment regimens achieve high rates of long-term relapse-free survival in treating acute promyelocytic leukemia (APL) and form the current standard of care. Refining prognostic estimates for newly diagnosed patients treated with ATO-containing regimens remains important in continuing to improve outcomes and identify patients who achieve suboptimal outcomes. We performed a pooled analysis of exclusively ATO-treated patients at a single academic institution and from the ALLG APML4 and Alliance C9710 studies to determine the prognostic importance of additional cytogenetic abnormalities and/or complex karyotype. We demonstrated inferior event-free survival for patients harboring complex karyotype (hazard ratio [HR], 3.74; 95% confidence interval [CI], 1.63-8.56; P = .002), but not for patients harboring additional cytogenetic abnormalities (HR, 2.13; 95% CI, 0.78-5.82; P = .142). These data support a role for full karyotypic analysis of all patients with APL and indicate a need for novel treatment strategies to overcome the adverse effect of APL harboring complex karyotype.

The Role of Human Epididymis Protein 4 in the Diagnosis and Prognosis of Diseases: An Umbrella Review of Systematic Reviews and Meta-Analyses of Observational Studies.

BackgroundThe application of human epididymis protein 4 (HE4) in diverse health diseases, especially in cancers, has been extensively studied in recent decades. To summarize the existing evidence of the aforementioned topic, we conducted an umbrella review to systematically evaluate the reliability and strength of evidence regarding the role of HE4 in the diagnostic and prognostic estimate of diverse diseases.MethodsElectronic searches in PubMed, Web of Science, and Embase databases were conducted from inception to September 16, 2021, for meta-analyses, which focus on the role of HE4 in the diagnosis and prognosis of diseases. This study protocol has been registered at PROSPERO (CRD42021284737). We collected the meta-analysis effect size of sensitivity, specificity, positive predictive value, and negative predictive value from diagnostic studies and gathered the hazard ratio (HR) of disease-free survival, overall survival, and progression-free survival from prognostic studies. For each systematic review and meta-analysis, we used a measurable tool for evaluating systematic reviews and meta-analysis (AMSTAR) to evaluate the methodological quality. Additionally, we assessed the quality of evidence on estimating the ability of HE4 in the diagnosis and prognosis of diverse diseases by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guideline.ResultsOverall, 20 meta-analyses including a total of 331 primary studies of different diseases were examined, mainly including ovarian cancer (OC) (n = 9), endometrial cancer (EC) (n = 6), and lung cancer (LC) (n = 4). The methodological qualities of all studies were rated as moderate (45%) or high (55%) by the AMSTAR. According to the GRADE, the certainties of 18 diagnostic pieces of evidence (9 for sensitivity and 9 for specificity) were rated as moderate (34%), low (33%), and very low (33%). Moreover, outcomes from prognosis studies showed evidence (1 for disease-free survival) with high certainty in regard to cancers (such as EC, OC, and LC) with the remaining three being moderate.ConclusionThis umbrella review suggested that HE4 was a favored biomarker in the prognosis of cancers, which was supported by high certainty of evidence. Additionally, HE4 could provide a suitable method for the diagnosis of EC, OC, and LC with moderate certainty evidence. Further large prospective cohort studies are needed to better elucidate the diagnostic and prognostic role of HE4 in diseases.

Percutaneous intravenous catheter forceps biopsy in right atrial mass: two case reports and literature review

BackgroundPrimary malignant tumors of the heart are rare. Although preoperative histological diagnosis is difficult, it has paramount value in therapeutic strategy development and prognostic estimation. Herein, we reported 2 cases of intracardiac tumors.Cases presentationBoth patients presented to the hospital with heart-related symptoms. Echocardiography showed massive masses in the atrium and positron emission tomography–computed tomography (PET/CT) revealed hypermetabolism and invasiveness. One patient cannot take surgery due to extensive metastasis and poor condition. The other patient was primarily diagnosed with lymphoma, and surgery was not recommended. They successfully underwent intravenous atrial biopsy, and histological samples confirmed intimal sarcoma and diffuse large B cell lymphoma. Based on immunohistochemical and molecular assessments, targeted chemotherapy was administered, resulting in clinical and imaging remission at discharge.ConclusionsPercutaneous intravenous catheter biopsy as a safe invasive test provides an accurate pathological diagnosis after imaging evaluation, and offers a therapeutic direction. Nonmalignant masses and some chemo-radiosensitive malignant tumors in the atrium could have good prognosis after targeted therapy.

Survival Estimation, Prognostic Factors Evaluation, and Prognostic Prediction Nomogram Construction of Breast Cancer Patients with Bone Metastasis in the Department of Bone and Soft Tissue Tumor: A Single Center Experience of 8 Years in Tianjin, China.

Purpose Bone metastasis in breast cancer remains globally concerned. Accurate survival estimation would be beneficial for clinical decision-making, especially for the patients with potential indications of surgery. Based on a retrospective cohort from China, the study aimed to construct a prognostic prediction nomogram for breast cancer patients with bone metastasis. Methods Breast cancer patients with bone metastasis diagnosed between 2009 and 2017 in our department were retrospectively selected. The total cohort was divided into construction and validation cohorts (ratio 7 : 3). A nomogram was constructed to predict the probability of survival, and the performance of model was validated. Results A total of 343 patients were enrolled with 243 and 100 patients in construction and validation cohorts, respectively. The median overall survival for the total cohort was 63.2 (95% CI: 52.4–74.0) months. Elevated ALP (HR = 1.71, 95% CI: 1.16–2.51; P=0.006), no surgery for breast cancer (HR = 2.19, 95% CI: 1.30–3.70; P=0.003), synchronous bone metastasis (HR = 1.98, 95% CI: 1.22–3.22; P=0.006), and liver metastasis (HR = 1.68, 95% CI: 1.20–2.37; P=0.003) were independent prognostic factors for worse survival. The independent predictors and other five factors (including age at diagnosis, ER status, PR status, Her-2 status, and the performance of bisphosphonate) were incorporated to construct the nomogram. The C-index was 0.714 (95% CI: 0.636–0.792) and 0.705 (95% CI: 0.705) in the construction cohort and validation cohort, respectively. All the calibration curves were close to the 45-degree line, which indicated satisfactory calibration. Conclusion A retrospective study aiming at prognostic estimation of breast cancer patients with bone metastasis was designed. Four independent prognostic factors were identified and a prognostic nomogram was constructed with satisfactory discrimination and calibration. The model could be used in survival estimation and individualized treatment planning.