Evidence map›Paper›PMID 28821205›Full record

ArticleNeuro-oncology2017

Cerebrospinal fluid circulating tumor cells: a novel tool to diagnose leptomeningeal metastases from epithelial tumors.

Xuling Lin, Martin Fleisher, Marc Rosenblum, Oscar Lin, Adrienne Boire, Samuel Briggs, Yevgeniya Bensman, Brenda Hurtado, Larisa Shagabayeva, Lisa M DeAngelis and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Neuro-oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
7.0field-weighted citation impact, top 2% 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

73 citing papers in PubMed, 114 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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

13 authors at 1 institution in 1 country.

Xuling LinDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Martin FleisherDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Marc RosenblumDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Oscar LinDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Adrienne BoireDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Samuel BriggsDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Yevgeniya BensmanDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Brenda HurtadoDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Larisa ShagabayevaDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Lisa M DeAngelisDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Katherine S PanageasDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Antonio OmuroDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Elena I PentsovaDepartment of Neurology, Department of Laboratory Medicine, Department of Pathology, and Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundDiagnosis of leptomeningeal metastasis (LM) remains challenging due to low sensitivity of CSF cytology and infrequent unequivocal MRI findings. In a previous pilot study, we showed that rare cell capture technology (RCCT) could be used to detect circulating tumor cells (CTC) in the CSF of patients with LM from epithelial tumors. To establish the diagnostic accuracy of CSF-CTC in the diagnosis of LM, we applied this technique in a distinct, larger cohort of patients.

methodsIn this institutional review board-approved prospective study, patients with epithelial tumors and clinical suspicion of LM underwent CSF-CTC evaluation and standard MRI and CSF cytology examination. CSF-CTC enumeration was performed through an FDA-approved epithelial cell adhesion molecule-based RCCT immunomagnetic platform. LM was defined by either positive CSF cytology or imaging positive for LM. ROC analysis was utilized to define an optimal cutoff for CSF-CTC enumeration.

resultsNinety-five patients were enrolled (36 breast, 31 lung, 28 others). LM was diagnosed in 30 patients (32%) based on CSF cytology (n = 12), MRI findings (n = 2), or both (n = 16). CSF-CTC were detected in 43/95 samples (median 19.3 CSF-CTC/mL, range 0.3 to 66.7). Based on ROC analysis, 1 CSF-CTC/mL provided the best threshold to diagnose LM, achieving a sensitivity of 93%, specificity of 95%, positive predictive value 90%, and negative predictive value 97%.

conclusionsWe defined ≥1 CSF-CTC/mL as the optimal cutoff for diagnosis of LM. CSF-CTC enumeration through RCCT is a robust tool to diagnose LM and should be considered in the routine LM workup in solid tumor patients.

Indexed as

Neoplastic Cells, CirculatingAdultAgedAged, 80 and overBiomarkers, TumorFemaleHumansMaleMeningeal NeoplasmsMiddle AgedNeoplasm MetastasisNeoplasms, Glandular and EpithelialBiomarkers, Tumorcerebrospinal fluidcirculating tumor cellsleptomeningeal metastases

Identifiers

PMID28821205
PMCPMC5570249
OpenAlexW2609108571

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.