Prognostic value of abnormally expressed long non-coding RNAs in patients with osteosarcoma: a meta-analysis
Bibliographic record
Abstract
// Fashuai Wu 1, * , Deyao Shi 1, * , Shidai Mu 2 , Yu Huang 3 , Feng Gao 1 , Xiangcheng Qing 1 and Zengwu Shao 1 1 Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China 2 Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China 3 Department of Otorhinolaryngology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China * These authors contributed equally to this work Correspondence to: Zengwu Shao, email: profszw1962@163.com Keywords: lncRNA; osteosarcoma; prognosis; biomarker; meta-analysis Received: May 23, 2017 Accepted: December 26, 2017 Published: January 12, 2018 ABSTRACT Long non-coding RNAs (lncRNAs) contribute to progression of various cancers including osteosarcoma through abnormal regulation of cancer-related cellular processes. Recent researches have shown that various lncRNAs are abnormally expressed in osteosarcoma and associated with the prognosis. With the aim of gaining a better insight into the association between expression level of lncRNAs and prognosis of osteosarcoma, multiple databases including PubMed, Embase, Cochrane Library and Web of Science were carefully searched for available studies up to March 14, 2017. Finally, 19 publications with 1298 patients matched our inclusion criteria and were evaluated in our meta-analysis. The quality of each study was scored using the Newcastle-Ottawa Scale and studies not reaching a minimum threshold were excluded. Results of the meta-analysis demonstrated that abnormal expression level of lncRNAs predicted poor overall survival (pooled HR 3.064, 95% CI: 2.487–3.775) and event-free survival (pooled HR 2.642, 95% CI 1.759–3.970) in osteosarcoma and subgroup analysis showed consistent prognostic value. Furthermore, combining data of Cox multivariable analysis indicated that abnormal expression level of lncRNAs was an independent prognostic marker for overall survival (pooled HR 2.864, 95% CI: 2.246–3.651) in osteosarcoma patients. The clinicopathological parameters analysis further showed that abnormal expression level of lncRNAs was correlated with tumor size, tumor stage, metastasis and differentiation grade of osteosarcoma. Limitations of the meta-analysis included variation of cut-off value definition, Chinese provenance of most studies, publication bias and so on. In conclusion, this meta-analysis suggested that abnormal expression level of lncRNAs has a promising future for predicting the prognosis of patients with osteosarcoma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.012 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".