Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literature
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
9 authors at 1 institution in 1 country.
Limin LiDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0001-8669-4653
Bing MaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0001-6908-4167
Fubin LiuDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0001-9370-3861
Chao ShengDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0003-2823-854X
Yu PengDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0001-6442-0803
Yating QiaoDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0002-7324-0115
Peng WangDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0003-4803-2549
Kexin ChenDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0003-4248-7681
Fangfang SongDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Tianjin, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.ORCID https://orcid.org/0000-0003-3998-8506
Tianjin Medical University Cancer Institute and Hospital · CN
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itself
Abstract
Purpose: The clinical application of combined tumor markers is still limited. We aim to explore the value of the combination of multiple tumor markers in gastric cancer (GC) prognosis. Methods: The prognostic significance was evaluated using Kaplan-Meier log-rank survival analysis and multivariable Cox regression analysis. The estimated area under the curve (AUC) was compared to evaluate the discriminatory ability of different indicators. A nomogram was constructed based on the results of multivariable cox regression, and its performance was evaluated by Harrell's concordance index and calibration curve. Results: NPTM (number of positive tumor markers) displayed independent prognostic significance whether in the whole cohort or in patients with different stages. Patients with the all-negative tumor markers had a worse prognosis after postoperative chemotherapy in all cohort ( Conclusions: NPTM was an independent predictor of gastric cancer prognosis, showing more accurate prognostic performance than individual tumor markers. Especially its significance in guiding postoperative adjuvant chemotherapy regimens and predicting prognosis by combination with TNM staging system may have a better clinical application value.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
The Number of Positive Tumor Markers (NPTM) Achieves Higher Value in the Prognosis Prediction of Gastric Cancer. · full record | OpenQuestion