Prior malignancy impact on survival outcomes of glioblastoma multiforme; population-based study

Al‐Husseini, Muneer J.; Saad, Anas M.; El-Shewy, Kholoud M.; Nissan, N.E.; Gad, Mohamed M.; Alzuabi, Muayad; Alfaar, Ahmad Samir

doi:10.1080/00207454.2018.1538989

Cited by 11 publications

(9 citation statements)

References 24 publications

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“…Studies evaluating prognostic factors showed that age, tumor histology, molecular markers, race, sex, education, marital status, treatment in high-volume and/or urban centers, insurance status, EOR, RCT, and tumor location impacted outcomes. 52 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 Although a few studies simply described general demographic changes of GBMs, 112 113 most studied specific questions. 52 55 56 57 58 59 60 61…”

Section: Resultsmentioning

confidence: 99%

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Utility of Administrative Databases and Big Data on Understanding Glioma Treatment—A Systematic Review

Owens

Nguyen

Karsy

2022

Indian Journal of Neurosurgery

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Background Gliomas are a heterogeneous group of tumors where large multicenter clinical and genetic studies have become increasingly popular in their understanding. We reviewed and analyzed the findings from large databases in gliomas, seeking to understand clinically relevant information. Methods A systematic review was performed for gliomas studied using large administrative databases up to January 2020 (e.g., National Inpatient Sample [NIS], National Surgical Quality Improvement Program [NSQIP], and Surveillance, Epidemiology, and End Results Program [SEER], National Cancer Database [NCDB], and others). Results Out of 390 screened studies, 122 were analyzed. Studies included a wide range of gliomas including low- and high-grade gliomas. The SEER database (n = 83) was the most used database followed by NCDB (n = 28). The most common pathologies included glioblastoma multiforme (GBM) (n = 67), with the next category including mixes of grades II to IV glioma (n = 31). Common study themes involved evaluation of descriptive epidemiological trends, prognostic factors, comparison of different pathologies, and evaluation of outcome trends over time. Persistent health care disparities in patient outcomes were frequently seen depending on race, marital status, insurance status, hospital volume, and location, which did not change over time. Most studies showed improvement in survival because of advances in surgical and adjuvant treatments. Conclusions This study helps summarize the use of clinical administrative databases in gliomas research, informing on socioeconomic issues, surgical outcomes, and adjuvant treatments over time on a national level. Large databases allow for some study questions that would not be possible with single institution data; however, limitations remain in data curation, analysis, and reporting methods.

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Section: Resultsmentioning

confidence: 99%

“…52 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 Although a few studies simply described general demographic changes of GBMs, 112 113 most studied specific questions. 52 55 56 57 58 59 60 61 62 63 64 65 66…”

Section: Resultsmentioning

confidence: 99%

Utility of Administrative Databases and Big Data on Understanding Glioma Treatment—A Systematic Review

Owens

Nguyen

Karsy

2022

Indian Journal of Neurosurgery

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“…Notably, the impact of prior malignancies on outcomes has been examined across several cancer types including glioblastoma, colorectal, lung, pancreatic, and uterine cancer [ 5 , 15 , 16 , 17 , 18 , 19 ] The incidence of older patients with prior malignancies ranged from 7% to 25% across these disease sites, generally without differences in cancer-specific survival, irrespective of whether patients had prior malignancy diagnoses [ 5 , 15 , 16 , 17 , 18 , 19 , 20 ]. Only one of the aforementioned studies, on colorectal cancer (CRC) [ 16 ], noted poorer overall survival (OS) among patients with non-leukemic prior cancers (although CRC-specific survival was improved in these patients); the remaining studies showed no OS difference based on patients’ prior malignancy status [ 5 , 15 , 17 , 18 ]. These data suggest that inclusion of patients with prior malignancies may not impact disease-related outcomes, including survival.…”

Section: Discussionmentioning

confidence: 99%

Association between Prior Malignancy Exclusion Criteria and Age Disparities in Cancer Clinical Trials

Patel

Parisi

Verma

et al. 2022

Cancers

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Prior malignancy exclusion criteria (PMEC) are often utilized in cancer clinical trials; however, the incidence of PMEC and the association of PMEC with trial participant age disparities remain poorly understood. This study aimed to identify age disparities in oncologic randomized clinical trials as a result of PMEC. Using a comprehensive collection of modern phase III cancer clinical trials obtained via ClinicalTrials.gov, we assessed the incidence and covariates associated with trials excluding patients with prior cancers within 5+ years from registration (PMEC-5). Using the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database, we further sought to determine the correlation between PMEC-5 and age disparities. PMEC-5 were used in 41% of all trials, with higher PMEC-5 utilization among industry-supported trials as well as trials evaluating a targeted therapy. Comparing trial patient median ages with population-matched median ages by disease site and time-period, we assessed the association between PMEC-5 and age disparities among trial participants. PMEC-5 were independently associated with heightened age disparities, which further worsened with longer exclusionary timeframes. Together, PMEC likely contribute to age disparities, suggesting that eligibility criteria modernization through narrower PMEC timeframes may work toward reducing such disparities in cancer clinical trial enrollment.

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“…Low-grade gliomas: 7.3 years [18]. High-grade gliomas: 18 months [18]; glioblastoma multiforme is the most lethal form (median survival: 10-15 months) [4][5][6].…”

Section: Gliomasmentioning

confidence: 99%

“…Gliomas represent 75% of malignant gliomas [ 3 ], and glioblastoma multiforme is the most lethal form. In fact, the prognosis of patients affected by glioblastoma multiforme remains a death sentence, with a median survival of 10–15 months [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Peptide Receptor Radionuclide Therapy and Primary Brain Tumors: An Overview

et al. 2021

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Primary brain tumors (PBTs) are some of the most difficult types of cancer to treat, and despite advancements in surgery, chemotherapy and radiotherapy, new strategies for the treatment of PBTs are needed, especially for those with poor prognosis such as inoperable/difficult-to-reach lesions or relapsing disease. In regard to the last point, malignant primary brain tumors remain some of the most lethal types of cancer. Nuclear medicine may provide exciting new weapons and significant contributions in the treatment of PBTs. In this review, we performed literature research in order to highlight the possible role of peptide receptor radionuclide therapy (PRRT) in the treatment of PBTs with radiolabeled molecules that bind with high-affinity transmembrane receptors such as somatostatin receptors (SSTRs), neurokinin type-1 receptor and prostate-specific membrane antigen (PSMA). These receptors are overexpressed in some cancer types such as gliomas, meningiomas, pituitary tumors and medulloblastomas. A comprehensive overview of possible applications in this field will be shown, providing knowledge about benefits, feasibility, developments and limitations of PRRT in this type of tumor, also revealing new advantages in the management of the disease.

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Prior malignancy impact on survival outcomes of glioblastoma multiforme; population-based study

Cited by 11 publications

References 24 publications

Utility of Administrative Databases and Big Data on Understanding Glioma Treatment—A Systematic Review

Utility of Administrative Databases and Big Data on Understanding Glioma Treatment—A Systematic Review

Association between Prior Malignancy Exclusion Criteria and Age Disparities in Cancer Clinical Trials

Peptide Receptor Radionuclide Therapy and Primary Brain Tumors: An Overview

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