Can we satisfactorily measure the clinical value of new oncology agents with a single summary measure?

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 6606-6606
Author(s):  
Clare Frances Jones ◽  
Giles Monnickendam ◽  
Mingshu Zhu ◽  
Jan McKendrick
Keyword(s):  
Median Survival ◽  
Clinical Benefit ◽  
Survival Benefit ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Survival Rates ◽  
Clinical Decision ◽  
Summary Statistics ◽  
Survival Curves ◽  
Clinical Value

6606 Background: Current value frameworks (VFs) assess clinical value primarily through using clinical trial endpoints as survival metrics (e.g., median and hazard ratio (HR)). But, if key assumptions do not hold, the interpretation of these summary statistics can become problematic and fail to adequately capture the expected benefit to a patient. This has been observed with innovative oncology treatments. As a proof of concept analysis, we reviewed how two VFs (ASCO and ESMO) dealt with cases where the assumption of proportional hazards (PH) does not hold. Methods: Oncology agents approved by the FDA since 2011 were reviewed and three agents were identified with survival profiles where the assumption of PH was found not to hold because, on visual inspection, the survival curves displayed non-standard patterns: Divergence followed by convergence – panobinostat OS in RRMM; Curves initially track together then diverge – nivolumab OS in NSCLC; Curves diverge steadily then a plateau emerged in the active treatment curve – pembrolizumab PFS in refractory melanoma. We evaluated these agents to assess which measures of clinical benefit were most valued under each VF and how the issue of non-PH influenced the outcome. Results: Clinical benefit/value scores varied: ASCO: 14-27 (maximum 100), ESMO: grade 1-3. The ASCO VF uses a hierarchical approach (incorporating HR and median survival benefit, always prioritising the former) adding a bonus for survival benefit in the tail of the distribution. The combination of HR, median survival benefit 2 and 3 year survival rates in the ESMO non-curative VF can potentially capture aspects of clinical benefit in some cases of non-PH. Overall, the ASCO VF appears less flexible to accommodate non-PH than the ESMO VF. Conclusions: Despite VFs using summary statistics which cannot be easily interpreted under conditions of non-PH, the case of non-PH is not explicitly catered for. Additionally, both VFs may miss important interpretation where value is differentiated across patients groups with different response profiles which may underlie non-standard survival curves. In these situations, a more flexible approach to assessing clinical value may render VFs more relevant for clinical decision making.

scholarly journals Clinical value of measurable residual disease testing for assessing depth, duration, and direction of response in multiple myeloma

2020 ◽  
Vol 4 (14) ◽  
pp. 3295-3301
Author(s):  
Joaquin Martinez-Lopez ◽  
Sandy W. Wong ◽  
Nina Shah ◽  
Natasha Bahri ◽  
Kaili Zhou ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Clinical Decision Making ◽  
Residual Disease ◽  
Clinical Care ◽  
Progression Free Survival ◽  
Clinical Decision ◽  
Routine Practice ◽  
Clinical Value ◽  
The Impact ◽  
Measurable Residual Disease

Abstract Few clinical studies have reported results of measurable residual disease (MRD) assessments performed as part of routine practice. Herein we present our single-institution experience assessing MRD in 234 multiple myeloma (MM) patients (newly diagnosed [NDMM = 159] and relapsed [RRMM = 75]). We describe the impact of depth, duration, and direction of response on prognosis. MRD assessments were performed by next-generation sequencing of immunoglobulin genes with a sensitivity of 10−6. Those achieving MRD negativity at 10−6, as well as 10−5, had superior median progression-free survival (PFS). In the NDMM cohort, 40% of the patients achieved MRD negativity at 10−6 and 59% at 10−5. Median PFS in the NDMM cohort was superior in those achieving MRD at 10−5 vs <10−5 (PFS: 87 months vs 32 months; P < .001). In the RRMM cohort, 36% achieved MRD negativity at 10−6 and 47% at 10−5. Median PFS was superior for the RRMM achieving MRD at 10−5 vs <10−5 (PFS: 42 months vs 17 months; P < .01). Serial MRD monitoring identified 3 categories of NDMM patients: (A) patients with ≥3 MRD 10−6 negative samples, (B) patients with detectable but continuously declining clonal numbers, and (C) patients with stable or increasing clonal number (≥1 log). PFS was superior in groups A and B vs C (median PFS not reached [NR], NR, 55 respectively; P < .001). This retrospective evaluation of MRD used as part of clinical care validates MRD as an important prognostic marker in NDMM and RRMM and supports its use as an endpoint in future clinical trials as well as for clinical decision making.

Identification of High-Risk Patients Among Those Diagnosed With Thin Cutaneous Melanomas

2007 ◽  
Vol 25 (9) ◽  
pp. 1129-1134 ◽  
Author(s):  
Phyllis A. Gimotty ◽  
David E. Elder ◽  
Douglas L. Fraker ◽  
Jeffrey Botbyl ◽  
Kimberly Sellers ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Tumor Cell ◽  
Clinical Decision Making ◽  
Classification Tree ◽  
Survival Rates ◽  
Clinical Decision ◽  
Mitotic Rate ◽  
Lesion Group ◽  
Pigmented Lesion ◽  
Ajcc Staging

Purpose Most patients with melanoma have microscopically thin (≤ 1 mm) primary lesions and are cured with excision. However, some develop metastatic disease that is often fatal. We evaluated established prognostic factors to develop classification schemes with better discrimination than current American Joint Committee on Cancer (AJCC) staging. Patients and Methods We studied patients with thin melanomas from the US population-based Surveillance, Epidemiology, and End Results (SEER) cancer registry (1988 to 2001; n = 26,291) and those seen by the University of Pennsylvania's Pigmented Lesion Group (PLG; 1972 to 2001; n = 2,389; Philadelphia, PA). AJCC prognostic factors were thickness, anatomic level, ulceration, site, sex, and age; PLG prognostic factors also included a set of biologically based candidate prognostic factors. Recursive partitioning was used to develop a SEER-based classification tree that was validated using PLG data. Next, a new PLG-based classification tree was developed using the expanded set of prognostic factors. Results The SEER-based classification tree identified additional criteria to explain survival heterogeneity among patients with thin, nonulcerated lesions; 10-year survival rates ranged from 89.1% to 99%. The new PLG-based tree identified groups using level, tumor cell mitotic rate, and sex. With survival rates from 83.4% to 100%, it had better discrimination. Conclusion Prognostication and related clinical decision making in the majority of patients with melanoma can be improved now using the validated, SEER-based classification. Tumor cell mitotic rate should be incorporated into the next iteration of AJCC staging.

How to Decide Whether to Offer and Use “Nonstandard” Therapies in Patients with Advanced Sarcomas and Gastrointestinal Stromal Tumors: Global Variations in Clinical Practice, Assessment, and Access to Therapies in Diseases with Limited Incidence and Data

2012 ◽  
pp. 645-650 ◽  
Author(s):  
Stefan Sleijfer ◽  
Ian Judson ◽  
George D. Demetri
Keyword(s):  
Clinical Practice ◽  
Rare Diseases ◽  
Clinical Benefit ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Base ◽  
Stromal Tumors ◽  
Appropriate Care ◽  
Social Interests ◽  
Practice Assessment

Overview: As cancer is more generally recognized as a collection of various rare diseases rather than a homogeneous illness, sarcomas have become a model for the manner in which data can and cannot be used to drive clinical decision making. In this article, we explore the limitations of data generated in rare diseases such as sarcomas to provide an evidence base for clinical practice. How should patients be treated if there is no “standard” that offers “proof” of clinical benefit? By asking this question, we also raise the issue of what constitutes “clinical benefit”—and how to measure that—for patients with sarcomas and other rare diseases. As physicians become more accountable for decisions—and yet are always accountable to the patients and families who rely on them to provide the best and most appropriate care—oncologists must be cognizant of the limitations of data in rare diseases and be ready to justify actions that are in the best medical and social interests of patients.

Value of precision medicine in advanced NSCLC: Real-world outcomes associated with the use of companion diagnostics.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20015-e20015
Author(s):  
Ani John ◽  
Roma Shah ◽  
William Bruce Wong ◽  
Charles Schneider ◽  
Hamid H. Gari ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Real World ◽  
Proportional Hazards ◽  
Survival Rates ◽  
Prognostic Index ◽  
Cox Proportional Hazards ◽  
Advanced Stage ◽  
Clinical Value ◽  
The Real

e20015 Background: Five-year survival rates as low as 2.8% have been reported in patients with non-small cell lung cancer (NSCLC), highlighting the need for individualized diagnosis and treatment. Companion diagnostic testing (CDx) identifies patients with molecular targets likely to respond better to particular therapies; however, not all cancer patients receive CDx in the real-world setting. This study evaluated the clinical value of CDx in the real world with respect to overall survival among patients with non-squamous advanced (Stage IIIB/IV) NSCLC (aNSCLC). Methods: Patients were from the Flatiron Health electronic health-derived database, treated with systemic therapy, and diagnosed with aNSCLC between January 1, 2011 and May 31, 2018; those who received CDx with their first line of treatment were compared with those who did not. Logistic regression using components of the modified Lung Cancer Prognostic Index (LCPI; age, sex, stage, actionable mutation(s), smoking, respiratory comorbidity; Alexander et al. Br J Cancer. 2017) and other factors were used to predict characteristics associated with receiving CDx. Overall survival was evaluated using Kaplan-Meier analysis. Unadjusted and adjusted Cox proportional hazards regression models were used to evaluate the association between CDx and overall survival. Results: A total of 17,143 patients with aNSCLC (CDx, n = 14,389; no CDx, n = 2754) and a mean (SD) age at diagnosis of 67.2 (10.0) years (CDx, 67.1 [10.1]; no CDx, 67.5 [9.2]) were included. There were more nonsmokers in the CDx group (17.4%) than the no CDx group (5.5%). Patients who were female, diagnosed after 2014, receiving multiple lines of therapy or had advanced stage at diagnosis were more likely to receive CDx. Patients receiving CDx had decreased mortality risk (unadjusted HR [95% CI] = 0.54 [0.52-0.57]) and lived longer than those not receiving CDx (median survival = 14 vs 7 months). The significant reduction in mortality associated with CDx remained after adjusting for factors included in the modified LCPI (adjusted HR [95% CI] = 0.78 [0.75-0.82]) as well as a model without actionable mutations (adjusted HR [95% CI] = 0.70 [0.66-0.73]). Conclusions: Among patients with non-squamous aNSCLC, use of CDx was associated with reduced risk of mortality compared with no CDx.

scholarly journals Systematic Review: A Prevention-Based Model of Neuropsychological Assessment for Children With Medical Illness

2017 ◽  
Vol 42 (8) ◽  
pp. 815-822 ◽  
Author(s):  
Kristina K. Hardy ◽  
Katie Olson ◽  
Stephany M. Cox ◽  
Tess Kennedy ◽  
Karin S. Walsh
Keyword(s):  
Clinical Decision Making ◽  
Adaptive Functioning ◽  
Survival Rates ◽  
Clinical Decision ◽  
Medical Illness ◽  
Individual Level ◽  
Care Models ◽  
Neuropsychological Changes ◽  
The Central Nervous System ◽  
The Individual

Abstract Objective Many pediatric chronic illnesses have shown increased survival rates, leading to greater focus on cognitive and psychosocial issues. Neuropsychological services have traditionally been provided only after significant changes in the child’s cognitive or adaptive functioning have occurred. This model of care is at odds with preventative health practice, including early identification and intervention of neuropsychological changes related to medical illness. We propose a tiered model of neuropsychological evaluation aiming to provide a preventative, risk-adapted level of assessment service to individuals with medical conditions impacting the central nervous system based on public health and clinical decision-making care models. Methods Elements of the proposed model have been used successfully in various pediatric medical populations. We summarize these studies in association with the proposed evaluative tiers in our model. Results and Conclusions This model serves to inform interventions through the various levels of assessment, driven by evidence of need at the individual level in real time.

scholarly journals Biologic Drug Survival in Psoriasis: A Systematic Review & Comparative Meta-Analysis

2020 ◽  
Author(s):  
Ahmed I Mourad ◽  
Robert Gniadecki
Keyword(s):  
Real World ◽  
Survival Data ◽  
Clinical Decision Making ◽  
Meta Analysis ◽  
Survival Rates ◽  
Clinical Decision ◽  
Drug Discontinuation ◽  
Large Variability ◽  
Drug Survival ◽  
Biologic Drug

Background: Drug survival studies have been utilized to evaluate the real-world effectiveness of biologics used in psoriasis. However, the increasing volume of drug survival data suffers from large variability due to regional differences in drug availability, patient selection and biologic reimbursement. Objectives: To conduct a meta-analysis of biologic drug survival to determine comparative effectiveness of the biologics in a real-world setting. Methods: Studies reporting drug survival for biologic therapy in psoriasis were identified by a systematic literature search. Hazard ratio data for drug discontinuation were estimated directly from published Kaplan-Meier estimator curves at year 1, 2 and 5 of treatment and compared pairwise for the following biologics: ustekinumab, adalimumab, etanercept, infliximab, secukinumab and ixekizumab. This pooled hazard ratios were used to estimate 2- and 5- year overall drug survival rates. Results: Ustekinumab had the longest persistence at 2 years and 5 years among all biologics included in this meta-analysis. Adalimumab was superior to etanercept and infliximab at 5 years. Pooled 5-year drug survival rates for adalimumab, etanercept, and infliximab were 46.3%, 35.9% and 34.7%, respectively. 2- and 5-year data were not available for anti-IL-17 drugs, but at 1-year ustekinumab outperformed secukinumab, the latter being equal to anti-TNFs. Conclusions: Ustekinumab is characterized by longer drug survival than TNF inhibitors and IL-17 inhibitors. Estimated pooled 2- and 5- year drug survival rates may serve as a useful tool for patient communication and clinical decision-making.

scholarly journals Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinjie Wu ◽  
Yanlei Wang ◽  
Wei Sun ◽  
Mingsheng Tan
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Training Group ◽  
Clinical Decision ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Predictive Values

Introduction. We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. Methods. The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes ( C -indexes) and calibration plots. Results. All 813 patients were randomly divided into a training group ( n = 572 ) and a validation group ( n = 241 ). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C -indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. Conclusions. The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making.

scholarly journals A Death-Related Gene Signature for Prognosis with Osteosarcoma

2021 ◽  
Author(s):  
Bin Xie ◽  
Shiyong Tan ◽  
Chao Li ◽  
Junyang Liang
Keyword(s):  
Regulatory Networks ◽  
Clinical Decision Making ◽  
Prognostic Biomarker ◽  
Survival Rates ◽  
Clinical Decision ◽  
Gene Signature ◽  
Rna Seq ◽  
Survival Group ◽  
Patient Prognosis ◽  
Death Group

Abstract Purpose: Osteosarcoma is one of the most prevalent malignancies, and despite significant advances in its treatment, patient prognosis remains poor and survival rates are low. It is undoubtedly important to explore the possible reasons for the low survival rates of patients and to reveal the differences.Methods and Results: We obtained RNA-Seq (HT seq) and clinical characteristics of osteosarcoma patients from the TCGA database and divided them into survival group and death group. We defined the differentially expressed genes (DEGs) between the two groups as death-related genes (DRGs) and used them to construct a prognostic signature for overall survival of patients with osteosarcoma. The results of the validation demonstrated satisfactory accuracy and predictive prognostic value of the model. In addition, we performed a series of bioinformatic analyses that identified two key genes and the regulatory networks they constituted that may play a role in the progression of osteosarcoma.Conclusion: Our DRGs signature represents a novel and clinically useful prognostic biomarker for patients with osteosarcoma, helping to aid clinical decision-making.

Understanding engagement and potential impact of an electronic drug repository: A mixed-methods study. (Preprint)

2021 ◽  
Author(s):  
Charlene Soobiah ◽  
Michelle Phung ◽  
Mina Tadrous ◽  
Trevor Jamieson ◽  
R. Sacha Bhatia ◽  
...  
Keyword(s):  
Online Survey ◽  
Clinical Decision Making ◽  
Point Of Care ◽  
Digital Health ◽  
Inappropriate Prescribing ◽  
Clinical Decision ◽  
Qualitative Description ◽  
Structured Interviews ◽  
Clinical Value ◽  
Secondary Information

BACKGROUND Centralized drug repositories can reduce adverse events and inappropriate prescribing by enabling access to dispensed medication data at the point-of-care, but how they achieve this goal is largely unknown. OBJECTIVE To understand 1) the perceived clinical value; 2) the barriers and enablers to adoption; and 3) for which clinician groups a provincial, centralized drug repository may provide the most benefit. METHODS A mixed-method approach, including an online survey and semi-structured interviews, was employed. Participants were clinicians (e.g., nurses, physicians, and pharmacists) in Ontario who were eligible to use the Digital Health Drug Repository (DHDR), irrespective of actual use. Survey data were ranked on a 7-point adjectival scale and analyzed using descriptive statistics and interviews were analyzed using qualitative description. RESULTS : Of 167 survey respondents, only 24% (n=40) were actively using the DHDR. Perceptions of the utility of the DHDR were neutral (mean scores ranged from 4.11-4.76). Of the 76% who were not using the DHDR, 98% rated access to medication information (e.g., dose, strength, frequency) as important. Reasons for not using the DHDR included the cumbersome access process and the perception that available data was incomplete or inaccurate. A total of 33 interviews were completed, of which 26 were active DHDR users. The DHDR was a satisfactory source of secondary information, but the absence of medication instructions and prescribed medications (that were not dispensed) limited its ability to provide a comprehensive profile in order to meaningfully support clinical decision-making. CONCLUSIONS Digital drug repositories must adjust to align with clinician needs to provide value. Ensuring (1) integration with point-of-care systems; (2) comprehensive clinical data; and (3) streamlined onboarding processes would optimize clinically meaningful use. The electronic provision of accessible drug information to providers across healthcare settings has the potential to improve efficiency and reduce medication errors. CLINICALTRIAL N/A

Discovery and validation of a cross-platform 21-gene prognostic signature in neuroblastoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10035-10035
Author(s):  
Mehul Gupta ◽  
Sunand Nageswaran Kannappan ◽  
Aru Narendran ◽  
Pinaki Bose
Keyword(s):  
Machine Learning ◽  
Risk Stratification ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Risk Model ◽  
Learning Algorithm ◽  
Clinical Decision ◽  
Gene Signature ◽  
Cox Proportional Hazards ◽  
Transcriptomic Signature

10035 Background: Neuroblastoma (NB) is the most common extracranial solid tumor in children. Despite the development of risk stratification tools to improve prognostication, prediction of patient survival outcomes in NB remains poor. In this study we used an unbiased machine-learning algorithm to develop and validate a transcriptomic signature capable of predicting 5-year overall (OS) and event-free survival (EFS) in these patients. Methods: The TARGET-Neuroblastoma dataset (n = 243) was used as the training set. Two independent NB cohorts, E-MTAB-179 (n = 478) and GSE85047 (n = 266) were used as validation sets. Elastic net regression was employed to identify transcripts associated with EFS. Association of the developed signature with EFS and OS was evaluated using univariate Cox proportional hazards (CoxPH), Kaplan-Meier, and 5-year receiver-operator characteristic curves in validation cohorts. Further, the independent prognostic value of the signature was assessed using multivariate CoxPH models with relevant clinicopathologic variables including age, INSS stage, and N-Myc amplification status in both validation sets. Finally, a nomogram was developed to integrate the signature with prognostic clinicopathologic variables to evaluate their combined efficacy for prediction of 5-year EFS and OS. Results: We identified a 21-gene signature that demonstrates significant association with EFS and OS in both E-MTAB-178 and GSE49710 validation cohorts. Moreover, the signature is independent of clinicopathological variables and can be effectively incorporated into a risk model, improving the prognostic performance. Several genes within the signature have been previously implicated in NB, including ECEL1, HOXC9 and ARAF1. Conclusions: To the best of our knowledge, we are the first to use an unbiased machine learning approach to generate a transcriptomic gene signature for neuroblastoma prognosis externally validated in multiple cohorts across platforms. This 21-gene transcriptomic signature significantly associated with EFS and OS in this disease. Combining this signature with current prognostic clinicopathologic variables will improve risk stratification of affected patients and may inform effective clinical decision-making.[Table: see text]

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