Bringing NASA Technology Down to Earth

Whether putting rovers on Mars or sustaining life in extreme conditions, NASA develops technologies to solve some of the most difficult challenges ever faced. Through its Technology Transfer Program, the agency makes the innovations behind space exploration available to industry, academia, and the general public. This paper describes the primary mechanisms through which NASA disseminates technology to solve real-life problems; illustrates recent program accomplishments; and provides examples of spinoff success stories currently impacting everyday life

A Sustainable Method for Quantifying the Benefits of NASA Technology Transfer

Since NASA's creation, technologies developed to advance NASA missions have found secondary applications, leading to products, services, and processes that create jobs, generate profits, improve efficiencies, and even save and improve lives. Despite a general consensus that these "spinoff" benefits are prevalent, no consistent methodology, analytic framework, or sustainable system has been established to quantify their benefits using standardized measurements. Over the years many efforts have attempted to quantify benefits. Each, however, has had limitations including scope, data integrity, and sustainability. NASA has historically recorded its benefits anecdotally in its annual Spinoff report with qualitative discussions and ad hoc quantification, but has not developed a systematic method for capturing quantifiable benefits. This paper describes a new approach that NASA is developing to systematically and routinely capture quantitative benefits from its Spinoff stories each year, using a framework that is sustainable over time. Surveying approximately 200 commercialized technologies recently featured in Spinoff, NASA has developed a suite of standard categories that can be used to quantify benefits. By surveying firms represented by those stories in Spinoff, NASA was able to collect additional quantitative data retrospectively. NASA will use these new categories to collect and standardize reporting data each year, as the stories are collected and developed. While not comprehensive of all benefits generated by the Nation's investment in space research and technology, this new analytic framework provides a sustainable and consistent source of data from the top technology transfer successes published in Spinoff each year, with the data coming directly from the firms that are commercializing NASA technologies. The new quantification categories include: jobs created; revenue generated; productivity and efficiency improvements; lives saved/not lost; and lives improved

Estimating survival in patients with gastrointestinal cancers and brain metastases: An update of the graded prognostic assessment for gastrointestinal cancers (GI-GPA).

BackgroundPatients with gastrointestinal cancers and brain metastases (BM) represent a unique and heterogeneous population. Our group previously published the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) for patients with GI cancers (GI-GPA) (1985-2007, n = 209). The purpose of this study is to update the GI-GPA based on a larger contemporary database.MethodsAn IRB-approved consortium database analysis was performed using a multi-institutional (18), multi-national (3) cohort of 792 patients with gastrointestinal (GI) cancers, with newly-diagnosed BM diagnosed between 1/1/2006 and 12/31/2017. Survival was measured from date of first treatment for BM. Multiple Cox regression was used to select and weight prognostic factors in proportion to their hazard ratios. These factors were incorporated into the updated GI-GPA.ResultsMedian survival (MS) varied widely by primary site and other prognostic factors. Four significant factors (KPS, age, extracranial metastases and number of BM) were used to formulate the updated GI-GPA. Overall MS for this cohort remains poor; 8 months. MS by GPA was 3, 7, 11 and 17 months for GPA 0-1, 1.5-2, 2.5-3.0 and 3.5-4.0, respectively. >30% present in the worst prognostic group (GI-GPA of ≤1.0).ConclusionsBrain metastases are not uncommon in GI cancer patients and MS varies widely among them. This updated GI-GPA index improves our ability to estimate survival for these patients and will be useful for therapy selection, end-of-life decision-making and stratification for future clinical trials. A user-friendly, free, on-line app to calculate the GPA score and estimate survival for an individual patient is available at brainmetgpa.com

Estimating Survival in Melanoma Patients With Brain Metastases: An Update of the Graded Prognostic Assessment for Melanoma Using Molecular Markers (Melanoma-molGPA).

PurposeTo update the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) for a markedly heterogeneous patient population, patients with melanoma and brain metastases, using a larger, more current cohort, including molecular markers.MethodsThe original Melanoma-GPA is based on data from 483 patients whose conditions were diagnosed between 1985 and 2005. This is a multi-institutional retrospective database analysis of 823 melanoma patients with newly diagnosed brain metastases from January 1, 2006, to December 31, 2015. Multivariable analyses identified significant prognostic factors, which were weighted and included in the updated index (Melanoma-molGPA). Multiple Cox regression was used to select and weight prognostic factors in proportion to their hazard ratios to design the updated Melanoma-molGPA in which scores of 4.0 and 0.0 are associated with the best and worst prognoses, as with all of the diagnosis-specific GPA indices. Log-rank tests were used to compare adjacent classes.ResultsThere were 5 significant prognostic factors for survival (age, Karnofsky performance status [KPS], extracranial metastases [ECM], number of brain metastases, and BRAF status), whereas only KPS and the number of brain metastases were significant in the original Melanoma-GPA. Median survival improved from 6.7 to 9.8 months between the 2 treatment eras, and the median survival times for patients with Melanoma-molGPA of 0 to 1.0, 1.5 to 2.0, 2.5 to 3.0, and 3.5 to 4.0 were 4.9, 8.3, 15.8, and 34.1 months (P<.0001 between each adjacent group).ConclusionsSurvival and our ability to estimate survival in melanoma patients with brain metastases has improved significantly. The updated Melanoma-molGPA, a user-friendly tool to estimate survival, will facilitate clinical decision making regarding whether and which treatment is appropriate and will also be useful for stratification of future clinical trials. To further simplify use, a free online/smart phone app is available at brainmetgpa.com

The Prognostic Value of BRAF, C-KIT, and NRAS Mutations in Melanoma Patients With Brain Metastases.

PurposeBrain metastases are a common problem in patients with melanoma, but little is known about the effect of gene mutations on survival in these patients.Methods and materialsWe created a retrospective multi-institutional database of 823 patients with melanoma and brain metastases diagnosed between 2006 and 2015. Clinical parameters, gene mutation status (BRAF, C-KIT, NRAS), and treatment were correlated with survival. Treatment patterns and outcomes were compared with a prior era (1985-2005).ResultsBRAF status was known in 584 of 823 patients (71%). BRAF, NRAS, and C-KIT mutations were present in 51%, 22%, and 11% of tested patients, respectively. The median time from primary diagnosis to brain metastasis was 32 months, and overall median survival (MS) from the time of initial treatment of brain metastases was 10 months. MS for BRAF-positive and BRAF-negative patients was 13 months and 9 months, respectively (P=.02). There was no significant difference in MS in patients with or without NRAS or C-KIT mutations. The time from primary diagnosis to brain metastasis did not vary by mutation and was not associated with survival after the diagnosis of brain metastases. MS for the 1985 to 2005 and 2006 to 2015 cohorts was 6.7 months and 10.0 months, respectively (P<.01). Reflecting treatment-trend changes, use of whole-brain radiation therapy decreased from 48% to 26% during this period. Among BRAF-positive patients, 71% received targeted BRAF and/or MEK inhibitors and 57% received some combination of targeted therapy, chemotherapy, and/or immunotherapy.ConclusionsFor melanoma patients with brain metastases, BRAF-positive patients survive longer than BRAF-negative patients and overall survival has improved from 1985-2005 to 2006-2015

Survival and prognostic factors in patients with gastrointestinal cancers and brain metastases: have we made progress?

The literature describing the prognosis of patients with gastrointestinal (GI) cancers and brain metastases (BM) is sparse. Our group previously published a prognostic index, the Graded Prognostic Assessment (GPA) for GI cancer patients with BM, based on 209 patients diagnosed from 1985-2005. The purpose of this analysis is to identify prognostic factors for GI cancer patients with newly diagnosed BM in a larger contemporary cohort. A multi-institutional retrospective IRB-approved database of 792 GI cancer patients with new BM diagnosed from 1/1/2006 to 12/31/2016 was created. Demographic data, clinical parameters, and treatment were correlated with survival and time from primary diagnosis to BM (TPDBM). Kaplan-Meier median survival (MS) estimates were calculated and compared with log-rank tests. The MS from time of first treatment for BM for the prior and current cohorts were 5 and 8 months, respectively (P < 0.001). Eight prognostic factors (age, stage, primary site, resection of primary tumor, Karnofsky Performance Status (KPS), extracranial metastases, number of BM and Hgb were found to be significant for survival, in contrast to only one (KPS) in the prior cohort. In this cohort, the most common primary sites were rectum (24%) and esophagus (23%). Median TPDBM was 22 months. Notably, 37% (267/716) presented with poor prognosis (GPA 0-1.0). Although little improvement in overall survival in this cohort has been achieved in recent decades, survival varies widely and multiple new prognostic factors were identified. Future work will translate these factors into a prognostic index to facilitate clinical decision-making and stratification of future clinical trials