Combining hematoxylin and eosin (H&E) stained images and RNA sequencing (RNA-Seq) data to predict overall survival (OS) in patients with non-small cell lung cancer (NSCLC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1547-1547
Author(s):  
Teresa M Karrer ◽  
Marius Garmhausen ◽  
Xiao Li ◽  
Gunther Jansen
Keyword(s):  
Clinical Trial ◽  
Gene Selection ◽  
Hazard Model ◽  
Cox Proportional Hazard Model ◽  
Proportional Hazard ◽  
Rna Seq ◽  
Proportional Hazard Model ◽  
Survival Group ◽  
Cox Proportional Hazard ◽  
Complementary Value

1547 Background: IMpower150 was a phase 3 clinical trial that evaluated the efficacy of atezolizumab in patients with metastatic nonsquamous NSCLC; it demonstrated no significant OS benefit in the ACP (atezolizumab+carboplatin+paclitaxel) arm vs the BCP (bevacizumab+carboplatin+paclitaxel) control arm (hazard ratio [HR]=0.85; 95%CI, 0.71-1.03). The objective of this analysis was to identify a subpopulation of patients that benefits from ACP using H&E stained images and RNA-Seq data. Methods: Spatial statistics algorithms were applied to the coordinates of tumor cells and lymphocytes of the H&E stained images to capture spatial heterogeneity of the tumor microenvironment. The normalized and log-transformed RNA-Seq data underwent a nested feature selection procedure using a Cox proportional hazard model with L1 regularization and stability selection. Cutoffs for gene selection were determined using a permutation strategy with a false discovery rate <0.001. To investigate the association between the 41 derived spatial features, significant genes and OS, a Cox proportional hazard model with L2 regularization was fitted only for the ACP group. Survival groups were further identified using nested Monte Carlo Cross Validation to prevent over-fitting. Results: A total of 236 ACP and 235 BCP patients who had both H&E stained images and RNA-Seq data were analyzed. In the predicted long survival group, ACP patients had significantly longer median OS vs BCP patients based on H&E stained images (HR=0.61; 95%CI, 0.41-0.90; P=0.013) and RNA-Seq data (HR=0.64; 95%CI, 0.41-0.99; P=0.042). The combination of both modalities further improved the OS benefit between the arms (HR=0.44; 95%CI, 0.27-0.73; P=0.001). Data-driven selection of genes relevant for the prediction of OS included MAML3, AC024475.4, RGPD1, LCE3D and AC004156.1. Conclusions: Our approach was able to stratify a subpopulation of patients that significantly benefited from ACP compared with BCP treatment, particularly when integrating both H&E stained images and RNA-Seq data, which demonstrated the complementary value of both modalities. Our results could inform the development of a companion diagnostic that predicts individualized treatment response. Clinical trial information: NCT02366143.

scholarly journals A Study of Factors Affecting the Length of Hospital Stay of COVID-19 Patients by Cox-Proportional Hazard Model in a South Indian Tertiary Care Hospital

2021 ◽  
Vol 12 ◽  
pp. 215013272110002
Author(s):  
Gayathri Thiruvengadam ◽  
Marappa Lakshmi ◽  
Ravanan Ramanujam
Keyword(s):  
Hospital Stay ◽  
Tertiary Care ◽  
Length Of Hospital Stay ◽  
Hazard Model ◽  
Cox Proportional Hazard Model ◽  
Care Hospital ◽  
Proportional Hazard ◽  
Proportional Hazard Model ◽  
Cox Proportional Hazard ◽  
South Indian

Background: The objective of the study was to identify the factors that alter the length of hospital stay of COVID-19 patients so we have an estimate of the duration of hospitalization of patients. To achieve this, we used a time to event analysis to arrive at factors that could alter the length of hospital stay, aiding in planning additional beds for any future rise in cases. Methods: Information about COVID-19 patients was collected between June and August 2020. The response variable was the time from admission to discharge of patients. Cox proportional hazard model was used to identify the factors that were associated with the length of hospital stay. Results: A total of 730 COVID-19 patients were included, of which 675 (92.5%) recovered and 55 (7.5%) were considered to be right-censored, that is, the patient died or was discharged against medical advice. The median length of hospital stay of COVID-19 patients who were hospitalized was found to be 7 days by the Kaplan Meier curve. The covariates that prolonged the length of hospital stay were found to be abnormalities in oxygen saturation (HR = 0.446, P < .001), neutrophil-lymphocyte ratio (HR = 0.742, P = .003), levels of D-dimer (HR = 0.60, P = .002), lactate dehydrogenase (HR = 0.717, P = .002), and ferritin (HR = 0.763, P = .037). Also, patients who had more than 2 chronic diseases had a significantly longer length of stay (HR = 0.586, P = .008) compared to those with no comorbidities. Conclusion: Factors that are associated with prolonged length of hospital stay of patients need to be considered in planning bed strength on a contingency basis.

scholarly journals SMOKING STATUS AFFECTING SURVIVAL OF ADENOCARCINOMA LUNG CANCER PATIENTS IN KUALA LUMPUR, MALAYSIA

2017 ◽  
Vol 10 (9) ◽  
pp. 312
Author(s):  
Nida Sajid Ali Bangash ◽  
Natasha Hashim ◽  
Nahlah Elkudssiah Ismail
Keyword(s):  
Lung Cancer ◽  
Prognostic Significance ◽  
Hazard Model ◽  
Rank Test ◽  
Cox Proportional Hazard Model ◽  
Proportional Hazard ◽  
Kuala Lumpur ◽  
Proportional Hazard Model ◽  
Cox Proportional Hazard ◽  
Survival Difference

  Objective: Adenocarcinoma (AC) of the lung is now the most common histologic type of non-small cell lung cancer (NSCLC) worldwide since the past 20 years. This study was conducted to investigate survival difference among smoker and non-smoker lung AC patients.Methods: A retrospective observational study was conducted for 81 advanced NSCLC adult Malaysian patients in Radiotherapy and Oncology Clinic at Hospital Kuala Lumpur, Malaysia. A total of adult 30 Malaysian smokers and 51 non-smokers with lung AC were included. Ex-smokers were not included in the study. Demographic and clinical data were collected and described. For survival analysis, Kaplan–Meier test and log-rank test were used to calculate overall survival (OS) and analyse the difference in the survival curve. Cox proportional hazard model was used to identify prognostic significance of smoking status.Results: Non-smokers showed a significant association with female gender and Stage IV NSCLC. The median OS was higher for non-smokers (493 days) as compared to smokers (230 days). The Cox proportional hazard model showed higher hazard ratio for smokers.Conclusion: Non-smoking is an independent positive prognostic factor in lung AC.

scholarly journals Introduction of Two-Dose Mumps-Containing Vaccine into Routine Immunization Schedule in Quzhou, China, Using Cox-Proportional Hazard Model

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zhiying Yin ◽  
Canjie Zheng ◽  
Quanjun Fang ◽  
Xiaoying Gong ◽  
Guoping Cao ◽  
...  
Keyword(s):  
Hazard Model ◽  
Routine Immunization ◽  
Cox Proportional Hazard Model ◽  
Proportional Hazard ◽  
Immunization Schedule ◽  
Proportional Hazard Model ◽  
Cox Proportional Hazard ◽  
Kaplan Meier ◽  
Routine Immunization Schedule ◽  
Different Doses

Mumps is a vaccine-preventable disease caused by the mumps virus, but the incidence of mumps has increased among the children who were vaccinated with one-dose measles-mumps-rubella (MMR) in recent years. In this study, we analyzed the influence of different doses of mumps-containing vaccine (MuCV) against mumps using Cox-proportional hazard model. We collected 909 mumps cases of children who were born from 2006 to 2010 and vaccinated with different doses of MuCV in Quzhou during 2006-2018, which were all clinically diagnosed. Kaplan-Meier survival methods and Cox-proportional hazard model were used to estimate the hazard probabilities. Kaplan–Meier curves showed that the cumulative hazard of male and female has no difference; lower hazards were detected among those who were vaccinated with two-dose MuCV, born in 2006, and infected after supplementary immunization activities (SIA). Cox-proportional hazard regression suggested that onset after SIA, born in 2006, and vaccinated with two-dose MuCV were protective factors against infection even after adjusting for potential confounding effects. Our study showed that it was necessary to revise the diagnostic criteria of mumps and identify RT-PCR as the standard for mumps diagnosis in China. We suggested that routine immunization schedule should introduce two doses of MMR and prevaccination screening should be performed before booster immunization in vaccinated populations.

Ultra-Deep Targeted Sequencing Does Not Identify MM Patients with Different Prognosis: Results from a Randomized Phase II Clinical Trial

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2078-2078
Author(s):  
Yanira Ruiz-Heredia ◽  
Joaquín Martínez-López ◽  
Jose Carlos Martínez-Ávila ◽  
Beatriz Sanchez-Vega ◽  
Inmaculada Rapado ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Board Of Directors ◽  
Allele Frequency ◽  
Plasma Cells ◽  
Read Depth ◽  
Cox Proportional Hazard Model ◽  
Proportional Hazard ◽  
Proportional Hazard Model ◽  
Advisory Committees ◽  
Cox Proportional Hazard

Abstract Next-generation sequencing (NGS) has revealed new insight into the complexity of clonal and subclonal architecture of multiple myeloma (MM). The introduction of targeted studies allows the detection of mutations with very low allele frequencies at affordable price. However, there is few information about the prognostic impact of this mutational profile in series of homogeneously treated MM patients. In this study, we analyzed the most frequently mutated genes in MM from patients included in a randomized clinical trial applying the highest read depth to date. We performed a correlation study between our results and cytogenetics aberrations and clinical outcomes. We used Ampliseq Library Kit 2.0 to target 77 genes (M3Pv2.0 panel) related to critical pathophysiological pathways, associated to drug resistance or targetable with molecular drugs in MM. We sequenced DNA (15ng) from CD138+ purified plasma cells from 80 MM patients at diagnosis included in GEM2010MAS65 clinical trial. We sequenced at an average read depth of 1500X and using Ion Proton sequencer (Thermo Fisher, USA, PaloAlto, CA). We used Ion Reporter software applying in-house modifications in call variants process. We also sequenced DNA from CD138 negative population in 30% of patients in order to filter out potential artifacts and stablish conditions for excluding germline variants. We first fitted a cox-proportional hazard model to predict survival and a second approach using a penalized regression LASSO. We identified 137 gene mutations in the 80 patients analyzed, 54 mutations were predicted pathogenic by Shif and Poliphen and 65 have been described in COSMIC database. 85% of patients harbored at least 1 mutation. The most frequently mutated genes were KRAS (16%), DIS3 (15%), NRAS (13%), BRAF (6%), and TP53 (5%), accounting for the 54% of the total number of mutations. The most frequently mutated pathways were RAS and NFKB in 34% and 28% of patients respectively. Mutational allele frequency for KRAS, BRAF and TP53 was, in all cases, lower than 50% while DIS3 showed mutations in a broad range (from 2 to 85%). Only one patient presented one mutation in NRAS at 73 % of allele frequency. For patients with more than one mutation, two different scenarios have been found. Some patients showed several genes mutated in a similar allele frequency values. On the contrary, a complex subclonal structure was confirmed in 3 patients, with mutations at very different clonal frequency. CD138 negative fraction was sequenced to confirm that these mutations were exclusive of plasma cells. The first of them had two mutations in DIS3 at 8 and 53% of allele frequency, second in KRAS and DIS3 at 13 and 63% respectively and the third in NRAS and IFNGR2 at 5 and 37% respectively. We found no differences in the survival based on pathway, mutational allele frequency or number of mutations. We also investigated pairwise associations between events and we not found significant correlations (Figure 1). Cox-proportional hazard model only showed a negative impact in survival of patients with TP53 mutations. This ultra-deep targeted sequencing strategy is able to detect mutations in most of patients, at very low allele frequency and using a minimal amount of DNA. Despite of its huge capacity to detect mutations, we have not identified new prognostic factors in MM patients treated with highly efficient therapies. However, this study again confirms the complexity of the genomic landscape of MM and the great heterogeneity between patients. The role of theses mutations at relapse as well as in the subsequent treatment effectiveness remains unknown and should be preferably investigated in larger cohorts of homogeneously treated MM patients. Figure 1 Figure 1. Disclosures Martínez-López: Novartis: Honoraria, Speakers Bureau. Oriol:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Stewart:celgene: Consultancy.

Impact of timing of adjuvant chemotherapy initiation on survival in pancreatic adenocarcinoma.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 355-355 ◽  
Author(s):  
Sofia Palacio ◽  
Caroline Ripat ◽  
Heather Stuart ◽  
Danny Yakoub ◽  
Nipun B. Merchant
Keyword(s):  
Adjuvant Chemotherapy ◽  
Adjuvant Therapy ◽  
Pancreatic Adenocarcinoma ◽  
Surgical Resection ◽  
Hazard Model ◽  
Disease Stage ◽  
Cox Proportional Hazard Model ◽  
Proportional Hazard ◽  
Proportional Hazard Model ◽  
Cox Proportional Hazard

355 Background: Pancreatic adenocarcinoma (PDAC) is now the third leading cause of cancer death. Surgical resection followed by adjuvant chemotherapy has been the standard of care. Due to the significant risk of morbidity following pancreatic surgery, initiation of adjuvant chemotherapy is often delayed. Prior prospective adjuvant trials have suggested that adjuvant therapy can be initiated as late as 12 weeks without detriment, but data regarding the effectiveness of beginning adjuvant therapy beyond that time remains unknown. Methods: We retrospectivelyreviewed data from the National Cancer Data Base (2004-2014) and included adult patients (pts) with PDAC with pathologic stage I-IIB who underwent surgical resection with curative intent. The primary outcome was overall survival (OS) based on time to adjuvant chemotherapy post-surgery as defined by postoperative weeks. Data were analyzed using Cox proportional hazard model and Kaplan-Meier survival curves. Results: 5279 pts. had surgery alone and 4,537 pts. received adjuvant chemotherapy. The median age was 64 years. 52% were male, 88% were white, 46% were treated at comprehensive community cancer centers. The primary surgical approach was whipple procedure in 61% of pts. 63% pts. received single agent chemotherapy and the mean time from surgery to chemotherapy was 61 days. Adjuvant chemotherapy was associated with improved OS irrespective of disease stage compared to those undergoing surgery alone (median OS for surgery alone 14 months vs adjuvant chemotherapy 21 months, p < 0.001). Cox proportional hazard model controlling for stage, surgical technique, lymph node dissection and margin status revealed improved OS in pts. receiving adjuvant chemotherapy. No significant differences in OS were seen for pts. starting adjuvant chemotherapy at 3, 6, 9, 12, 16, 20 or 24 weeks after surgical resection. Conclusions: Current guidelines recommend initiation of adjuvant chemotherapy prior to 12 weeks after pancreatic resection. Initiating adjuvant chemotherapy even up to six months post-operatively improves OS compared to those undergoing surgery alone. Our data supports the use of adjuvant chemotherapy if indicated regardless of time of surgery.

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