Recurrent syncope, which patient should we follow more closely

Abstract Introduction The importance of education is well recognized in patients presenting with syncope, in order to reduce the recurrence rate. Purpose To determine a predictive score of recurrent syncopal episodes after the first medical assessment. Methods We conducted a retrospective study enrolling patients followed in our Syncope Consultation from January 2015 to November 2019. Clinical and episodes characteristics, as well as diagnostic studies were analysed. Correlation between variables was performed by the Chi-square and T-Student tests, with a significance level of 95%. Independent predictors of recurrent syncope were identified through a binary logistic regression analysis, considering p=0.05. Then, a discriminatory function was applied using the Wilks lambda test to determine the discriminant score of the analysed groups. SPSS 24.0 was used for statistical analysis. Results A total of 694 patients were included, and 420 (60.5%) had recurrent syncope at the first evaluation. After educational approach, 97 (14%) maintained recurrent episodes. In this subgroup, the mean age was 63.7±22.8 years-old and 88.7% already had previous recurrent syncope (vs 56.1%; p<0.001). The prodrome of malaise was common (40.2% vs 26.8%; p=0.008), but 32% of these patients had syncope without prodromes (vs 21.8%; p=0.032). They also had frequently first-degree atrioventricular (AV) block (22.5% vs 6.8%; p<0.001) and 51.7% had a final diagnosis of reflex syncope. No previous medication with calcium channel blockers (CCB) (p<0.001), malaise (p=0.011), not having Q-waves in the electrocardiogram (p=0.022) and the presence of first-degree AV block (p<0.001) were independent predictors of recurrent syncope. A predictive score of recurrence was determined using the formula: 0.108 − 1.556 x (medication with CCB) + 0.989 x (malaise) − 1.031 x (Q-waves) + 2.406 x (first degree AV block). Variables should be replaced by 1 or 0, depending on whether the condition is present or not. A cut-off of 0.283 was obtained with a specificity of 96.1% and a discriminative power of 81.2%. Conclusion In our patients presenting with syncope, recurrence rate reduced from 60,5% to 14% just with educational measures. To help identify patients who maintain recurrence, we determined a predictive score using clinical data from the first visit, with a good discriminative power and excellent specificity. It could be used to strengthen education, to direct diagnostic studies and to shorten follow-up visits, but it still needs validation to be used in clinical practice. Funding Acknowledgement Type of funding source: None

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P4579Prediction of CABG indication in patients admitted for NSTEMI with the new CABG DAPE2S score

European Heart Journal ◽

10.1093/eurheartj/ehz745.0967 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

T Faria Da Mota ◽

P Azevedo ◽

R Fernandes ◽

J S ◽

J Guedes ◽

...

Keyword(s):

Coronary Artery ◽

Risk Model ◽

Artery Bypass ◽

Bypass Graft ◽

Categorical Variables ◽

Binary Logistic Regression Analysis ◽

Continuous Variables ◽

Discriminant Score ◽

Significance Level ◽

Number Of Patients

Abstract Introduction A significant number of patients admitted for Non-ST Elevation Myocardial Infarction (NSTEMI) have multivessel complex coronary artery disease (CAD) and benefit from Coronary Artery Bypass Graft surgery (CABG). These patients frequently present high-risk surgical profiles, constituting a challenging group when it comes to balancing ischemic and haemorrhagic risk. Objective To develop a simple predictive risk model of referral to CABG in patients admitted for NSTEMI. Methods The authors present a retrospective, descriptive and correlational study including all patients admitted for NSTEMI in a Cardiology department between the 1st of October 2010 and the 1st of October 2018. Demographic profile, clinical characteristics, risk factors and hospitalization data of NSTEMI patients referred to CABG were studied, and a correlational analysis was performed with Chi-square test for categorical variables and t-Student test for continuous variables (confidence level of 95%). Independent predictors of CABG in patients with NSTEMI were identified through Binary logistic regression analysis, using a significance level of 0,05. A discriminatory function was subsequently applied, and the Wilks lambda test was used to determine the discriminant score for the studied groups. The authors used SPSS 24,0 for statistical analysis. Results A total of 2476 patients were included, 668 (27%) of which were female, with a mean age of 68,5±13,4 years. In the studied sample, 273 patients (11%) were proposed to CABG. The authors found a significant association between CABG and multiple clinical, laboratorial and therapeutical variables, but after multivariate analysis only male sex, previous Diabetes Mellitus, previous angina, previous Percutaneous coronary intervention, absence of a normal EKG, ST segment depression at admission, sinus rythm and brain natriuretic peptide (BNP) >100pg/mL proved to be independent predictors of referral. Using these variables, the authors developed a risk model to predict CABG referral in NSTEMI patients: −0,614 − (0,756 x female sex) + (0,305 x diabetes) + (0,631 x angina) − (1,513 x previous PCI) + (1,216 x sinus rythm) + (0,672 x ST depression) − (0,806 x normal EKG) + (0,562 x BNP>100). In this function, variables should be substituted by 1 or 0, depending on wheter the condition they specify is present or absent. The optimal discrimination cutoff was 0,23, with a 64% sensibility and 59% specificity, and a discriminant power of 60%. Conclusion Being able to predict referral to surgical revascularization in NSTEMI may help physicians to optimize a specific approach in each patient, in particular with regard to anti-thrombotic strategies. The authors developed a risk predicting model for CABG in NSTEMI patients based on simple clinical and laboratory variables, which will require validation in a larger cohort, before it can be applied in a clinical context.

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S-reflex score: a predictor score of vaso-vagal reflex syncope

European Heart Journal Acute Cardiovascular Care ◽

10.1093/ehjacc/zuab020.016 ◽

2021 ◽

Vol 10 (Supplement_1) ◽

Author(s):

H Costa ◽

R Fernandes ◽

T Mota ◽

J Bispo ◽

P Azevedo ◽

...

Keyword(s):

Clinical Investigation ◽

Descriptive Analysis ◽

High Specificity ◽

Final Diagnosis ◽

Categorical Variables ◽

Continuous Variables ◽

Discriminative Power ◽

Discriminant Score ◽

Significance Level ◽

Reflex Syncope

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Reflex syncope is one of the most common causes of syncope, usually associated with unspecified triggers and prodromes. The probability of occurrence is higher when concomitant factors coexist whether inherent to individual or related to environment, and changes in conventional tests may prove useful in their diagnosis. Objective Identify predictive factors in the initial investigation in order to establish a predictor score of vasovagal reflex syncope (VVS). Methods Observational and retrospective study, with descriptive analysis and correlation of patients followed in syncope appointment at a Cardiology Center from 1 January 2015 to 31 Novembe 2019. Descriptive analysis on patient characteristics and complementary exams were carried out. The correlation test used between categorical variables was Chi-square and among continuous variables the T-Student test with a significance level of 95%. Independent predictors of VVS were identified through binary logistic regression considering a p = 0.05, with subsequent application of a discriminatory function using the lambda Wilks test to determine the discriminant score of variables under analysis. SPSS 24.0 was used for statistical analysis. Results Identified N694 patients, 52% male, mean age of 63 years. 15.7% of patients with suspected VVS in a first impression. At the end, 22.9% diagnosed with VVS and of these 66% had syncope recurrence. 42% had long prodromes (p = 0.013), 17% with heat prodromes (p = 0.012), in 11.3% the trigger was the meal (p = 0.031), 12.2% suffered trauma (p = 0.07) and 59.7% had ECG with pathological q wave (p = 0.00), thus showing to be independet predictors of VVS. A predictor score of VVS was determined using the formula = -0.761 + (0.529.Long_Prodromes) + (0.721.Heat_Prodromes) + (0.313.Trigger_Meal) + (2,431.ECG_q) - (0.542.Trauma), with a cutoff value of 0.258, specificity of 90.5% with discriminative power of 87%. Conclusion The final diagnosis of VVS was higher than suspicions during initial clinical investigation and 66% of these patients had recurrence. The independent predictors factors of VVS are long prodromes, heat prodromes, meal as a trigger, ECG with q waves and trauma. The S-Reflex score was determined with a good discriminative power with high specificity. Considering clinical variables and conventional exams, this score could be useful to guide the strategy for syncope patients after the first evaluation to a more cost-effective strategy.

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P844NAS2H score, a novel predictive score of 1-year all cause mortality in Acute Coronary Syndromes

European Heart Journal ◽

10.1093/eurheartj/ehz747.0442 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

T Faria Da Mota ◽

J Sousa Bispo ◽

P Azevedo ◽

R Fernandes ◽

J P Guedes ◽

...

Keyword(s):

Acute Coronary Syndromes ◽

Left Ventricular ◽

Left Ventricular Ejection ◽

Predictive Score ◽

Categorical Variables ◽

Accurate Estimation ◽

Discriminant Score ◽

Previous Stroke ◽

Coronary Syndromes ◽

Discriminant Power

Abstract Introduction In patients admitted for Acute Coronary Syndromes (ACS), mortality is influenced by several clinical and therapeutical factors, and management of these patients should be guided by an estimate of individual risk. Objective To develop a simple predictive model of 1-year mortality in patients admitted for ACS. Methods The authors present a retrospective, descriptive and correlational study including all patients admitted for ACS in a Cardiology department between the 1st of October 2010 and the 1st of October 2017. A 1-year (1y) follow-up was made through registry consultation and phone call by a Cardiologist. Patients with 1y mortality (1yM) events were studied regarding baseline demographic and clinical characteristics, risk factors and hospitalization data, and a correlational analysis with Chi-square test for categorical variables and t-Student test for continuous variables (confidence level of 95%) was performed. Independent predictors of 1yM were identified through binary logistic regression analysis, using a significance level of 0,05. A discriminatory function was applied, and the Wilks lambda test was used to determine the discriminant score for the studied groups. The authors used SPSS 24,0 for statistical analysis. Results A total of 3251 patients were included, 826 (25,4%) of which were female, with a mean age of 65,5±13,4 years. In the studied sample, 268 patients (8,2%) died in the year following hospital discharge; this group had a mean age of 65,6±13,2 years, and 80 (29,9%) were female patients. There was a significant association between 1yM and multiple clinical, therapeutical and laboratorial variables, but after multivariate analysis only age greater than 65 years old (yo) [p=0,001], previous stroke [p=0,005], haemoglobin (Hb) <10mg/dL [p<0,001], brain natriuretic peptide (BNP) >100pg/mL [p=0,001], and left ventricular ejection fraction (LVEF) <50% [p <0,001] proved to be independent predictors of the studied outcome. Using these variables, the authors developed a scoring model to predict 1yM in patients admitted for ACS with the following formula = 0,002 + (0,736 x Age >65yo) + (0,91 x previous stroke) + (2,562 x Hb <10) + (0,63 x BNP >100) - (1,207 x FEVE >50%). In this function, variables should be substituted by 1 or 0, depending on wheter they are present or not. The discrimination cutoff was 0,57, with a 70,6% sensibility and 75,9% specificity, and a discriminant power of 75,4%. Conclusion Defining the mortality risk of ACS patients after discharge represents a real challenge and demands a careful evaluation of multiple factors in an attempt to achieve an accurate estimation of risk. The authors developed a predicting model for 1yM in ACS patients, with a good discriminant power, based on simple variables. The present score will require validation in a larger cohort of ACS patients before it can be applied in a clinical context.

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Relevansi Informasi Laporan Keuangan Accrual Basis: Kemampuan Rasio Keuangan Dalam Memprediksi Status Financial Distress Pemerintah Daerah Kabupaten Dan Kota Se- Indonesia Periode 2015-2017

JURNAL EKSPLORASI AKUNTANSI ◽

10.24036/jea.v1i2.111 ◽

2019 ◽

Vol 1 (2) ◽

pp. 795-813

Author(s):

Waninda Waninda ◽

Fefri Indra Arza

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Financial Distress ◽

Binary Logistic Regression ◽

City Government ◽

Performance Ratio ◽

Binary Logistic Regression Analysis ◽

Regional Government ◽

Significance Level

This study aims to predict the financial distress status of district and city governments in Indonesia. Research examines the relevance of financial statement information consisting of profitability ratio, liquidity ratio, performance ratio and capital stress ratio in predicting district and city government financial distress in Indonesia in 2015-2017. This study uses agency theory. The sampling method in this study used purposive sampling. This study consisted of 134 samples of districts / cities in Indonesia, the financial data used in the study were audited regional government financial reports, namely reports on audit results for 2015-2017. The type of data used is secondary data. The analysis used is binary logistic regression analysis. Based on the results of binary logistic regression analysis with a significance level of 5%, that of the four types of ratios measured using fourteen measurements obtained results (1) Profitability ratio as measured by profit margin ratio affects financial distress with an β coefficient of 51,548 and a significance value of 0,000 < 0.05, (2) The performance ratio measured by operating revenue to total revenue has an effect on financial distress with an β coefficient of -41.180 and a significance value of 0.015> 0.05, and a depreciation ratio influences financial distress with an β coefficient of 40.004 and a value significance of 0.004 <0.05

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Thermography screening of thyroid gland: how to distinguish health from pathology

Medical alphabet ◽

10.33667/2078-5631-2019-3-29(404)-32-39 ◽

2019 ◽

Vol 3 (29) ◽

pp. 32-39

Author(s):

I. M. Dolgov ◽

M. G. Volovik ◽

O. V. Nikitina ◽

T. P. Shkurat

Keyword(s):

Thyroid Gland ◽

Region Of Interest ◽

Binary Logistic Regression ◽

Binary Logistic Regression Analysis ◽

True Negative ◽

Significance Level ◽

Thyroid Pathology ◽

Negative Results ◽

Group 2 ◽

Group 1

This research is organized to investigate if the thermal gradient (Tgrad) (difference between temperature maximum and minimum in the region of interest over thyroid gland on neck thermogramm) could be a marker of normal/ abnormal thyroid function and, if so, find out the cut-off value and check it screening validity.Materials and methods. Thermography examination was performed using a TVS-300 med (S-Petersburg, Russia) thermal imaging camera with a resolution of 384 × 288 pixels and sensitivity was <0.04 °C according to European Association of Thermology standards. Anterior neck thermografic images were performed and collected in cloud database, where, by mean of program tools, region of interest were marked and Tgrad calculated. Totally 1025 pts with different thyroid pathology (group 1: female 944, age 15–90 (55,4±15,8), male 81, age 14–86 (53,6±18,8)), and 395 healthy persons (group 2: male 324 age 17–26 (21,8±4,4), female 71 age 16–70т (34,6±12,7)) were investigated. To check the quality of the model another 314 persons (18 male and 296 female) were studied in screening mode.Results. Calculated Tgrad value was 1,65±0,53 °C, Ме 1,53(1,24; 1,90) and 0,98±0,23 °C, Me 1,01(0,82; 1,15) for group 1 and 2 accordingly. By mean of binary logistic regression analysis we found good correlation between Tgrad value and presence/absence of thyroid pathology: significance level р<0,0001, χ² = 838,84, df = 1, β 0 = 9,984, β 1 = –9,033. Area under curve in ROC analysis was 0,922 (95 % CI 0,908; 0,935), р<0,001; optimal cut off value for Tgrad was 1,21 °C for maximal sensitivity (79,8 %) and specificity (83,3 %). In screening evaluation, according to optimal cut-off value 1,2 °C for Tgrad , 82,2 % of cases were classified correctly: true-positive and true-negative results were achieved in 258 from 314 pts.Conclusion. Thermography test, based on Tgrad value calculation, could help to distinguish persons with normal and abnormal function of thyroid gland.

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Hematocrit and impact of transfusion in patients receiving extracorporeal life support

Perfusion ◽

10.1177/0267659118772457 ◽

2018 ◽

Vol 33 (7) ◽

pp. 546-552 ◽

Cited By ~ 6

Author(s):

Justyna Swol ◽

Christopher Marschall ◽

Justus T. Strauch ◽

Thomas A. Schildhauer

Keyword(s):

Relative Risk ◽

Confidence Interval ◽

Life Support ◽

Extracorporeal Life Support ◽

Hospital Length ◽

Hospital Length Of Stay ◽

Entire Group ◽

Binary Logistic Regression Analysis ◽

Trauma Patients ◽

Significance Level

Introduction: Increasing the hematocrit is considered to increase oxygen delivery to the patient, especially when hypoxic conditions exist and the patient may become more stable. The aim of this study was to evaluate the relationship between hematocrit and hospital mortality via subgroup analyses of trauma and non-trauma patients. Methods: The hospital length of stay (LOS) and LOS in the intensive care unit (ICU) and hospital after extracorporeal life support (ECLS) treatment of 81 patients were analyzed and compared. In-hospital survival until extracorporeal membrane oxygen (ECMO) weaning and hospital discharge were defined as the clinical outcome. Results: Significantly increased mortality, with a relative risk of 1.73 with a 95% confidence interval of 1.134 to 2.639, was identified in the group with an hematocrit greater than 31%. However, no significant differences in relative risk (95% confidence interval) of death for each group were found among groups with an hematocrit less than or equal to 25%, 26-28% and 29-31%. Additionally, no significant relationship between survival and median hematocrit level was observed at a significance level of 0.413 and an Exp (B) of 1.089 at a 95% confidence interval of 0.878 to 1.373 in binary logistic regression analysis; a model was established with a -2 log likelihood of 40.687 for the entire group of patients. Moreover, a significant increase in mortality was observed as the average number of transfusions per day in the hospital increased (significance level 0.024, Exp (B) 4.378, 95% confidence interval for Exp (B) 1.212 to 15.810). Conclusion: Because a variety of factors influence therapy, the indication for transfusion should be re-evaluated and adapted repeatedly on a case-by-case basis. Further studies are needed to demonstrate whether an acceptable outcome from ECLS device therapy can also be achieved with a low hematocrit and a restrictive indication for transfusion.

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P1721Determination of a predictive score of cardiogenic shock in acute coronary syndrome

European Heart Journal ◽

10.1093/eurheartj/ehz748.0476 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

R Menezes Fernandes ◽

T Mota ◽

J Bispo ◽

P Azevedo ◽

J Guedes ◽

...

Keyword(s):

Acute Coronary Syndrome ◽

Mortality Rate ◽

Hospital Mortality ◽

Cardiogenic Shock ◽

Sinus Rhythm ◽

Left Ventricular ◽

Left Ventricular Ejection ◽

Predictive Score ◽

Discriminative Power ◽

Coronary Syndrome

Abstract Introduction Cardiogenic shock is one of the leading causes of death in patients with acute coronary syndrome (ACS), reaching in-hospital mortality rates of 50%. Purpose To identify a predictive score of cardiogenic shock in patients with ACS. Methods We performed a retrospective, descriptive and correlational study encompassing patients admitted with ACS in a Cardiology service from 1st October 2010 to 1st October 2018. Demographic factors, risk factors, antecedents and clinical characteristics were analyzed. The correlation between the categorical variables was performed by the Chi-square test, while the T-Student test was applied to the continuous variables, with a significance level of 95%. Independent predictors of cardiogenic shock were identified through a binary logistic regression analysis, considering p=0,05. Then, a discriminatory function was applied using the Wilks lambda test to determine the discriminant score of the analized groups. Statistical analysis was conducted with SPSS 24.0. Results During this period, 4458 patients were admitted with ACS and 74 (1,7%) developed cardiogenic shock. In this subgroup, 59,5% were over 65 years of age, 63,5% were male and 93,2% presented with acute myocardial infarction with ST segment elevation. Also, 83,8% were in sinus rhythm at admission, 22,7% had creatinine>1,5 mg/dL and 17,9% had left ventricular ejection fraction (LVEF) <30%. The in-hospital mortality rate was 51,4%. LVEF <30% (p=0,018), creatinine>1,5 mg/dL (p=0,044) and absence of sinus rhythm at admission (p=0,041) were independent predictors of cardiogenic shock. A predictive score of this complication in patients with ACS was determined using the formula: 1,723 + 1,505 x (creatinine>1,5) + 4,483 x (LVEF <30%) – 2,094 x (sinus rhythm at admission). A cutoff of 0,58 was obtained with 44,4% sensitivity, 85,2% specificity and 85% discriminative power. Conclusion Cardiogenic shock occurred in 1,7% of patients admitted with ACS and was associated with a high mortality rate. We determined a predictive score of this complication with a good discriminative power, which included LVEF <30%, creatinine >1,5 mg/dL and the rhythm on admission's electrocardiogram. By taking into account clinical variables, this score can be used at a very early stage of admission, allowing risk stratification of developing cardiogenic shock in each patient. However, it needs validation to be applied in clinical practice.

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Pengaruh Promosi dan Lokasi terhadap Keputusan Pembelian pada Cafe Tabik di Bukittinggi

JUSIE (Jurnal Sosial dan Ilmu Ekonomi) ◽

10.36665/jusie.v2i02.137 ◽

2018 ◽

Vol 2 (02) ◽

pp. 115-123

Author(s):

Nurfitriyenni Nurfitriyenni

Keyword(s):

Significant Influence ◽

Sampling Method ◽

Binary Logistic Regression ◽

Sampling Technique ◽

Simple Random Sampling ◽

Binary Logistic Regression Analysis ◽

Purchase Decisions ◽

Research Subject ◽

Purchasing Decisions ◽

Significance Level

This study aims to determine whether promotions and locations influence the purchasing decisions at Tabik Café and analyze the most dominant factors in influencing the purchasing decisions of Tabik Café in Bukittinggi. Samples taken were 100 respondents. Sampling in this study uses probability sampling technique with simple random sampling method, which is that each individual has the same opportunity to be used as a research subject. From the results of Binary Logistic Regression analysis shows that there is a positive and significant influence between promotion and location on Purchase Decisions. The results of testing the regression model with the dependent variable purchasing decision obtained by the equation Y = -13.770 + 0.259 X1 + 0.556 X2. From the results of the analysis obtained the significance level of each Promotion variable (X1) is 0.039, location (X2) is 0.001. The results of the analysis show that each variable has a positive and significant influence on purchasing decisions at Tabik Café in Bukittinggi.

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Multilevel predictors of controlled CD4 count and blood pressure in an integrated chronic disease management model in rural South Africa: a panel study

BMJ Open ◽

10.1136/bmjopen-2020-037580 ◽

2020 ◽

Vol 10 (11) ◽

pp. e037580

Author(s):

Soter Ameh ◽

Francesc X Gómez-Olivé ◽

Kathleen Kahn ◽

Stephen Tollman ◽

Kerstin Klipstein-Grobusch

Keyword(s):

South Africa ◽

Blood Pressure ◽

Chronic Disease ◽

Disease Management ◽

Chronic Disease Management ◽

Panel Study ◽

Binary Logistic Regression ◽

Cd4 Count ◽

Binary Logistic Regression Analysis ◽

Significance Level

ObjectiveIn 2011, The National Department of Health introduced the Integrated Chronic Disease Management (ICDM) model as a pilot programme in selected primary healthcare facilities in South Africa. The objective of this study was to determine individual-level and facility-level predictors of controlled CD4 count and blood pressure (BP) in patients receiving treatment for HIV and hypertension, respectively.DesignA panel study.Setting and participantsThis study was conducted in the Bushbuckridge Municipality, South Africa from 2011 to 2013. Facility records of patients aged ≥18 years were retrieved from the integrated chronic disease management (ICDM) pilot (n=435) and comparison facilities (n=443) using a three-step probability sampling process. CD4 count and BP control are defined as CD4 count >350 cells/mm3 and BP <140/90 mm Hg. A multilevel Least Absolute Shrinkage and Selection Operator binary logistic regression analysis was done at a 5% significance level using STATA V.16.Primary outcome measuresCD4 (cells/mm3) count and BP (mm Hg).ResultsCompared with the comparison facilities, patients receiving treatment in the pilot facilities had increased odds of controlling their CD4 count (OR=5.84, 95% CI 3.21–8.22) and BP (OR=1.22, 95% CI 1.04–2.14). Patients aged 50–59 (OR=6.12, 95% CI 2.14–7.21) and ≥60 (OR=7.59, 95% CI 4.75–11.82) years had increased odds of controlling their CD4 counts compared with those aged 18–29 years. Likewise, patients aged 40–49 (OR=5.73, 95% CI 1.98–8.43), 50–59 (OR=7.28, 95% CI 4.33–9.27) and ≥60 (OR=9.31, 95% CI 5.12–13.68) years had increased odds of controlling their BP. In contrast, men had decreased odds of controlling their CD4 count (OR=0.12, 95% CI 0.10–0.46) and BP (OR=0.21, 95% CI 0.19–0.47) than women.ConclusionThe ICDM model had a small but significant effect on BP control, hence, the need to more effectively leverage the HIV programme for optimal BP control in the setting.

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PIOS ratio: predicting the best response of non-small-cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e21507 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e21507-e21507

Author(s):

Foteinos-Ioannis D. Dimitrakopoulos ◽

Achilleas Nikolakopoulos ◽

Anastasia E Kottorou ◽

Elias Liolis ◽

Theodora Frantzi ◽

...

Keyword(s):

Immune Checkpoint ◽

Immune Checkpoint Inhibitors ◽

Checkpoint Inhibitors ◽

Performance Status ◽

Predictive Biomarker ◽

Outcome Data ◽

Predictive Score ◽

Binary Logistic Regression Analysis ◽

Best Response ◽

Nsclc Patients

e21507 Background: With the exception of programmed death ligand 1 (PD-L1) expression and Tumour Mutational Burden (TMB), which have entered clinical practice, no other clinically useful predictive biomarker for immune checkpoint inhibitors (ICIs) has been established in the daily practice. The purpose of this study was to develop a novel, non-interventional and clinically useful predictive score for NSCLC patients with advanced disease treated with ICIs. Methods: Eighty-nine patients with advanced and histologically confirmed NSCLC (stages III and IV), treated with immunotherapy (nivolumab, pembrolizumab, atezolizumab), were enrolled in the current study. Clinicopathological data as well response rates and clinical outcome data were collected. Based on this data and using a regression model, we developed a predictive score (Patras Immunotherapy Score-PIOS) with regard to the best response to ICIs. Best overall responses (BOR) were based on the immune-based therapeutics (iRECIST) criteria. Results: Four of the studied parameters -Performance Status (PS), Body Mass Index (BMI), age and lines of treatment (LOT)- were incorporated in our formula (PS *BMI/ LOT*age) giving rise to PIOS. This score was strongly associated with BOR, with patients of a good response (SD, PR or CR) having higher PIOS compared to patients with progression disease (PD) (p<0.001). The association remained significant when we used a four-tier model (PD, SD, PR and CR) for BOR (p<0.001). PIOS predictive significance also persisted using a binary logistic regression analysis (p=0.001). Conclusions: This study suggests that PIOS, which combines 4 baseline clinical parameters, may help to identify NSCLC patients with increased probability to be benefitted from ICIs treatment. Further evaluation and possibly combination with other factors may multiply its clinical significance.

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