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Cognitive and noncognitive predictors of success.

ABSTRACT: When predicting success, how important are personal attributes other than cognitive ability? To address this question, we capitalized on a full decade of prospective, longitudinal data from n = 11,258 cadets entering training at the US Military Academy at West Point. Prior to training, cognitive ability was negatively correlated with both physical ability and grit. Cognitive ability emerged as the strongest predictor of academic and military grades, but noncognitive attributes were more prognostic of other achievement outcomes, including successful completion of initiation training and 4-y graduation. We conclude that noncognitive aspects of human capital deserve greater attention from both scientists and practitioners interested in predicting real-world success.

SUBMITTER: Duckworth AL

PROVIDER: S-EPMC6876246 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Cognitive and noncognitive predictors of success.

Duckworth Angela L AL Quirk Abigail A Gallop Robert R Hoyle Rick H RH Kelly Dennis R DR Matthews Michael D MD

Proceedings of the National Academy of Sciences of the United States of America 20191104 47

When predicting success, how important are personal attributes other than cognitive ability? To address this question, we capitalized on a full decade of prospective, longitudinal data from <i>n</i> = 11,258 cadets entering training at the US Military Academy at West Point. Prior to training, cognitive ability was negatively correlated with both physical ability and grit. Cognitive ability emerged as the strongest predictor of academic and military grades, but noncognitive attributes were more p ...[more]

PMID: 31685624

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Project description:Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer, with approximately 50% of patients having residual disease after neoadjuvant chemotherapy (NACT) and worse prognosis with higher residual cancer burden (RCB). Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. There is a need for PDX models encompassing the heterogeneity of TNBC both pre- and post- therapy and for identifying clinical and molecular features of patient’s tumors that are associated with success in establishing these models. Using fine-needle aspirates (FNAs), we established orthotopic PDX models of TNBC from the primary breast tumors of patients prior to and following neoadjuvant systemic therapy while enrolled in the ARTEMIS trial (NCT02276443). ARTEMIS is a prospective neoadjuvant clinical trial for women with primary TNBC who are treated with four cycles of Adriamycin combined with cyclophosphamide (AC) followed by taxane +/- different experimental therapies. Serial biopsies were obtained from patients prior to treatment (pre-therapy), from poorly responsive disease after four cycles of AC (mid-NACT), and in cases of AC-resistance, after a three-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 FNA biopsies from 217 women, generating a total of 62 successful PDX models (overall success-rate = 23%). This cohort includes five serial pre- and mid-NACT PDX pairs, as well as one serial pre-, mid-, post-NACT triplet. Success of PDX engraftment was generally higher from cancers that proved to be treatment-resistant: whether poor response to AC determined by ultrasound measurements mid-NACT (p=0.063), RCB II/III status after NACT (p=0.046), or metastatic relapse within two years of surgery (p=0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumor revealed no significant association with PDX engraftment rate (p=0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient’s diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient’s tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC.

Dataset Information

Cognitive and noncognitive predictors of success.

Publications

Cognitive and noncognitive predictors of success.

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