scholarly journals Development and Validation of an Early Mortality Risk Score for Older Patients Treated with Chemotherapy for Cancer

2021 ◽  
Vol 10 (8) ◽  
pp. 1615
Author(s):  
Jaime Feliu ◽  
Alvaro Pinto ◽  
Laura Basterretxea ◽  
Borja López-San Vicente ◽  
Irene Paredero ◽  
...  
Keyword(s):  
Older Patients ◽  
Prognostic Score ◽  
External Validation ◽  
Early Death ◽  
Early Mortality ◽  
Background Estimation ◽  
Patients With Cancer ◽  
Validation Set ◽  
Ecog Ps ◽  
Development And Validation

Background: Estimation of life expectancy in older patients is relevant to select the best treatment strategy. We aimed to develop and validate a score to predict early mortality in older patients with cancer. Patients and Methods: A total of 749 patients over 70 years starting new chemotherapy regimens were prospectively included. A prechemotherapy assessment that included sociodemographic variables, tumor/treatment variables, and geriatric assessment variables was performed. Association between these factors and early death was examined using multivariable logistic regression. Score points were assigned to each risk factor. External validation was performed on an independent cohort. Results: In the training cohort, the independent predictors of 6-month mortality were metastatic stage (OR 4.8, 95% CI [2.4–9.6]), ECOG-PS 2 (OR 2.3, 95% CI [1.1–5.2]), ADL ≤ 5 (OR 1.7, 95% CI [1.1–3.5]), serum albumin levels ≤ 3.5 g/dL (OR 3.4, 95% CI [1.7–6.6]), BMI < 23 kg/m2 (OR 2.5, 95% CI [1.3–4.9]), and hemoglobin levels < 11 g/dL (OR 2.4, 95% CI (1.2–4.7)). With these results, we built a prognostic score. The area under the ROC curve was 0.78 (95% CI, 0.73 to 0.84), and in the validation set, it was 0.73 (95% CI: 0.67–0.79). Conclusions: This simple and highly accurate tool can help physicians making decisions in elderly patients with cancer who are planned to initiate chemotherapy treatment.

Development and validation of an early death risk score for older patients treated with chemotherapy for cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 12030-12030
Author(s):  
Jaime Feliu Batlle ◽  
Alvaro Pinto ◽  
Laura Basterretxea ◽  
Irene Paredero Pérez ◽  
Elisenda Llabres ◽  
...  
Keyword(s):  
Elderly Patients ◽  
Risk Score ◽  
Older Patients ◽  
Validation Cohort ◽  
External Validation ◽  
Early Death ◽  
Chemotherapy Treatment ◽  
Training Cohort ◽  
Death Risk ◽  
Patients With Cancer

12030 Background: Determining life expectancy in older patients is needed to select the best treatment strategy. We aimed to develop and validate a score to predict early death risk ( < 6 months) in elderly patients with cancer that are planned to initiate chemotherapy treatment. Methods: Patients over 70 years starting new chemotherapy regimens were prospectively included in a multicenter study. A pre-chemotherapy assessment that included sociodemographics, tumor/treatment variables, and geriatric assessment variables, was performed. Association between these factors and early death was examined by using multivariate logistic regression. Score points were assigned to each risk factor based on their b coefficient. We validated the risk score with an external validation cohort of 206 patients. Results: Three hundred forty two patients were included in the training cohort. The independent predictors for early death were metastasic cancers (odds ratio [OR] 4.8, 95% confidence interval [CI], [2.4-9.6]), ECOG performance status (OR 2.3, 95% CI:1.084-5.232), ADL (OR 1.7, 95% CI:1.08-3.5), serum albumin levels (3.3, 95% CI: 1.6-6.6), BMI (OR 2.4, 95% CI:1,2-4.8), serum GGT levels (OR 1.5, 95% CI:1.05-1.8) and hemoglobin levels (OR 2.3, 95% CI:1.2-4.6). With these results, a score was to stratify patients regarding their risk of early death: low (0 to 2 points; 5%), intermediate (3 to 5 points; 19%) or high (6 to 14 points; 50%) (p < 0.001). The area under the curve of the receiver-operating characteristic (ROC) curve was 0.79 for the training cohort (95% CI, 0.74 to 0.85), and 0.70 (95% CI: 0.60-0.80) for the validation cohort (difference between cohorts not statistically different). Conclusions: We developed a highly accurate tool that uses basic clinical and analytical information to predict the probability of early death in elderly patients with cancer that are planned to initiate chemotherapy treatment. This tool can help physicians in decision making for this population of patients.

scholarly journals One-Year Mortality in Older Patients with Cancer: Development and External Validation of an MNA-Based Prognostic Score

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0148523 ◽  
Author(s):  
Isabelle Bourdel-Marchasson ◽  
Abou Diallo ◽  
Carine Bellera ◽  
Christelle Blanc-Bisson ◽  
Jessica Durrieu ◽  
...  
Keyword(s):  
Older Patients ◽  
Prognostic Score ◽  
External Validation ◽  
Cancer Development ◽  
Patients With Cancer ◽  
One Year

scholarly journals Development and validation of a prognostic model for early triage of patients diagnosed with COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chansik An ◽  
Hyun Cheol Oh ◽  
Jung Hyun Chang ◽  
Seung-Jin Oh ◽  
Jung Mo Lee ◽  
...  
Keyword(s):  
Prognostic Score ◽  
External Validation ◽  
Vital Signs ◽  
Underlying Disease ◽  
Test Results ◽  
Additional Information ◽  
Patient Will ◽  
National Cohort ◽  
Evaluation Metric ◽  
Development And Validation

AbstractWe developed a tool to guide decision-making for early triage of COVID-19 patients based on a predicted prognosis, using a Korean national cohort of 5,596 patients, and validated the developed tool with an external cohort of 445 patients treated in a single institution. Predictors chosen for our model were older age, male sex, subjective fever, dyspnea, altered consciousness, temperature ≥ 37.5 °C, heart rate ≥ 100 bpm, systolic blood pressure ≥ 160 mmHg, diabetes mellitus, heart disease, chronic kidney disease, cancer, dementia, anemia, leukocytosis, lymphocytopenia, and thrombocytopenia. In the external validation, when age, sex, symptoms, and underlying disease were used as predictors, the AUC used as an evaluation metric for our model’s performance was 0.850 in predicting whether a patient will require at least oxygen therapy and 0.833 in predicting whether a patient will need critical care or die from COVID-19. The AUCs improved to 0.871 and 0.864, respectively, when additional information on vital signs and blood test results were also used. In contrast, the protocols currently recommended in Korea showed AUCs less than 0.75. An application for calculating the prognostic score in COVID-19 patients based on the results of this study is presented on our website (https://nhimc.shinyapps.io/ih-psc/), where the results of the validation ongoing in our institution are periodically updated.

Early death in older patients with cancer: risk factors of worse outcomes?

2013 ◽  
Vol 4 ◽  
pp. S85
Author(s):  
R. Boulahssass ◽  
V. Mari ◽  
S. Gonfrier ◽  
F. Auben ◽  
A. Abakar-Mahamat ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cancer Risk ◽  
Older Patients ◽  
Early Death ◽  
Cancer Risk Factors ◽  
Patients With Cancer

Prognostic value of routine biomarkers in older patients with cancer: Pooled analysis of three prospective cohorts.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 11551-11551
Author(s):  
Elena Paillaud ◽  
Pierre Soubeyran ◽  
Nadia Oubaya ◽  
Etienne Brain ◽  
Marianne Fonck ◽  
...  
Keyword(s):  
Overall Survival ◽  
Older Patients ◽  
Prognostic Value ◽  
Prognostic Score ◽  
Performance Status ◽  
Glasgow Prognostic Score ◽  
Pooled Analysis ◽  
Clinical Model ◽  
Patients With Cancer ◽  
Net Reclassification Improvement

11551 Background: To assess prognostic value of routine biomarkers in older patients with cancer. Methods: A pooled analysis of three prospective multicentre cohorts, ELCAPA, PHRC Aquitaine and ONCODAGE was conducted. Patients aged 70 years or older, with cancer were included. Biomarkers collected were plasmatic C-reactive protein, albumin and a combined score: Glasgow Prognostic Score (GPS). The GPS comprised three categories (0: CRP≤10 mg/L, albumin≥35 g/L; 1: CRP≤10 mg/L and albumin < 35 g/L, or CRP > 10 mg/L and albumin≥35 g/L; 2: CRP > 10 mg/L and albumin < 35 g/L).The primary endpoint was overall survival at 12 months. Multivariable Cox models were used, adjusting for age, sex, localisation, metastatic status, performance status, frailty screening index, the G8. Discriminative properties were assessed using Harrell C index and NRI (Net Reclassification Improvement). Results: Overall 1800 patients were analyzed (ELCAPA: N = 543, PHRC Aquitaine: N = 253, ONCODAGE: N = 1004; mean age: 78.5±5.5 years; 61.7% of men; 37% metastatic; most frequent localisations: breast (34.9%) and colon-rectum (17.7%); 70.7% of patients screened at risk of frailty with G8). Overall survival was 71.1%. GPS was independently associated with death (among normal G8: GPS 1: Hazard Ratio (HR) = 4.48; 95% Confidence Interval (95% CI) = [2.03; 9.89], GPS 2: 11.64 [4.54; 29.81], among abnormal G8: GPS 1: 2.45 [1.79; 3.34], GPS 2: 3.97 [2.93; 5.37]. The addition of GPS to the clinical model (Harell C: 0.82 [0.80; 0.83]) improved discrimination (Harell C: 0.84 [0.82; 0.85], NRI: 11% [5; 19]). Conclusions: GPS could be used in older patients with cancer to help decision-making and prognosis assessment.

Prognostic score for second or further line immunotherapy in advanced non-small cell lung cancer (aNSCLC): An external validation.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14077-e14077
Author(s):  
Arsela Prelaj ◽  
Giuseppe Lo Russo ◽  
Claudia Proto ◽  
Diego Signorelli ◽  
Roberto Ferrara ◽  
...  
Keyword(s):  
Prognostic Score ◽  
Performance Status ◽  
External Validation ◽  
Progression Free Survival ◽  
Best Supportive Care ◽  
Second Line ◽  
Ecog Performance Status ◽  
Prognostic Groups ◽  
Recorded Data ◽  
Ecog Ps

e14077 Background: Beyond PD-L1, nowadays oncologists can only use clinical characteristics to candidate patients for immunotherapy (IO). Previously, a clinical prognostic score composed by ECOG performance status (PS), sex, histology, stage, uses of platin-based therapy at first-line (1L) and response to 1L categorized 3 different prognostic groups for patients treated with second-line (2L) chemotherapy (CHT) (Di Maio, EJC. 2010 Mar;46(4):735-43.). The aim of this study is to assess if the same score is able to discriminate the outcome of aNSCLC pts treated in 2L or further-line IO, potentially helping decision making. Methods: We recorded data of patients collected from two institutional databases: Istituto Nazionale Tumori of Milan and IRCCS Oncologico Giovanni Paolo II of Bari, Italy. Overall survival (OS) was the primary endpoint and also progression-free survival (PFS) was assessed. Prognostic score was generated, and pts were divided into 3 prognostic groups: best (B: < 5), intermediate (I:5-9), worst (W: > 9). Results: Overall, 347 pts were included in the analysis (193 from Milan and 154 from Bari). Median age was 66 years (y) (30 – 88y), most were < 70 y (67.5%), male (70.7%), smokers (79.5%) and adenocarcinoma (74.6%). ECOG PS was: 0 (23%), 1 (54.5%) and 2 (22.5%). Pts distribution was: 28%, 51% and 21% in the B, I and W groups, respectively. Median OS was 18.0 months for B group, 8.5 months for I group (HR vs B 1.83, 95%CI 1.35 – 2.47, p < 0.001) and 2.6 months for W group (HR vs B 5.77, 95%CI 3.99 – 8.33, p < 0.001). Median PFS was 3.4 months for B group, 3.7 months for I group (HR vs B 1.35, 95% CI 1.03 – 1.77, p = 0.032) and 1.9 months for W group (HR vs B 2.51. 95% CI 1.80- 3.50, p < 0.001). Similar results were obtained stratifying the model by Institution. Conclusions: This clinical prognostic score, that was generated in patients treated with second-line chemotherapy, is able to highly predict outcomes of patients treated with IO. These results demonstrated that in pre-treated aNSCLC pts, the worst category has a dismal absolute life expectancy, and probably would not benefit from any active systemic therapy (independently if CHT or IO). Perhaps for these pts best supportive care could be the best choice.

Validation of a prognostic score for early mortality in severe head injury cases

2014 ◽  
Vol 121 (6) ◽  
pp. 1314-1322 ◽  
Author(s):  
Pedro A. Gómez ◽  
Javier de-la-Cruz ◽  
David Lora ◽  
Luis Jiménez-Roldán ◽  
Gregorio Rodríguez-Boto ◽  
...  
Keyword(s):  
Head Injury ◽  
High Risk ◽  
Risk Score ◽  
Prognostic Score ◽  
Early Death ◽  
Early Mortality ◽  
Final Model ◽  
Sum Score ◽  
The Impact ◽  
Very High

Object Traumatic brain injury (TBI) represents a large health and economic burden. Because of the inability of previous randomized controlled trials (RCTs) on TBI to demonstrate the expected benefit of reducing unfavorable outcomes, the IMPACT (International Mission on Prognosis and Analysis of Clinical Trials in TBI) and CRASH (Corticosteroid Randomisation After Significant Head Injury) studies provided new methods for performing prognostic studies of TBI. This study aimed to develop and externally validate a prognostic model for early death (within 48 hours). The secondary aim was to identify patients who were more likely to succumb to an early death to limit their inclusion in RCTs and to improve the efficiency of RCTs. Methods The derivation cohort was recruited at 1 center, Hospital 12 de Octubre, Madrid (1990–2003, 925 patients). The validation cohort was recruited in 2004–2006 from 7 study centers (374 patients). The eligible patients had suffered closed severe TBIs. The study outcome was early death (within 48 hours post-TBI). The predictors were selected using logistic regression modeling with bootstrapping techniques, and a penalized reduction was used. A risk score was developed based on the regression coefficients of the variables included in the final model. Results In the validation set, the final model showed a predictive ability of 50% (Nagelkerke R2), with an area under the receiver operating characteristic curve of 89% and an acceptable calibration (goodness-of-fit test, p = 0.32). The final model included 7 variables, and it was used to develop a risk score with a range from 0 to 20 points. Age provided 0, 1, 2, or 3 points depending on the age group; motor score provided 0 points, 2 (untestable), or 3 (no response); pupillary reactivity, 0, 2 (1 pupil reacted), or 6 (no pupil reacted); shock, 0 (no) or 2 (yes); subarachnoid hemorrhage, 0 or 1 (severe deposit); cisternal status, 0 or 3 (compressed/absent); and epidural hematoma, 0 (yes) or 2 (no). Based on the risk of early death estimated with the model, 4 risk of early death groups were established: low risk, sum score 0–3 (< 1% predicted mortality); moderate risk, sum score 4–8 (predicted mortality between 1% and 10%); high risk, sum score 9–12 (probability of early death between 10% and 50%); and very high risk, sum score 13–20 (early mortality probability > 50%). This score could be used for selecting patients for clinical studies. For example, if patients with very high risk scores were excluded from our study sample, the patients included (eligibility score < 13) would represent 80% of the original sample and only 23% of the patients who died early. Conclusions The combination of Glasgow Coma Scale score, CT scanning results, and secondary insult data into a prognostic score improved the prediction of early death and the classification of TBI patients.

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