Evidence map›Paper›PMID 17568813›Full record

ReviewLeukemia2007

The role of prognostic factors in assessing 'high-risk' subgroups of patients with chronic lymphocytic leukemia.

N E Kay, S M O'Brien, A R Pettitt, S Stilgenbauer

Abstract readReview
PubMed Publisher
In one paragraph

Review in Leukemia, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

38 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. The prognostic role of HBV infection in chronic lymphocytic leukemia.Journal of cancer research and clinical oncology · 2018
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  18. Downregulation of IL-17-producing T cells is associated with regulatory T cell expansion and disease progression in chronic lymphocytic leukemia.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2013
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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

4 authors.

N E KayDivision of Hematology, Mayo Clinic, Rochester, MN, USA. kay.neil@mayo.edu
S M O'Brien
A R Pettitt
S Stilgenbauer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The management of chronic lymphocytic leukemia (CLL) has historically relied on 'watchful waiting' and palliative approaches to therapy. However, the course of disease is highly variable and a substantial proportion of patients with early-stage CLL develop rapidly progressive disease requiring therapy. In recent decades, numerous clinical and biological prognostic markers that are predictive of decreased survival outcomes, disease progression and/or resistance to therapy, and that may play a role in defining the subgroups of patients with 'high-risk' CLL have been identified. At the same time, highly effective treatment modalities have become available with the advent of chemoimmunotherapy combinations and allogeneic stem cell transplantation. Thus, we are approaching an era when patients with CLL may potentially benefit from individualized risk assessments based on prognostic markers and when specific therapies may be offered to the subgroup of patients with high-risk disease. This review provides a brief overview of newer biological prognostic markers, discusses the challenges associated with identifying the subgroup of patients with high-risk CLL and further aims to provide recommendations on how prognostic markers may be used to assess high-risk subgroups in different clinical situations in CLL.

Indexed as

Biomarkers, TumorImmunotherapyHumansLeukemia, Lymphocytic, Chronic, B-CellPrognosisRisk FactorsBiomarkers, Tumor

Identifiers

PMID17568813

What OpenQuestion holds

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Registered trials

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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.