Evidence map›Paper›PMID 29064026›Full record

ReviewCurrent hematologic malignancy reports2017

Models of Prognostication in Chronic Myelomonocytic Leukemia.

Francesco Onida

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current hematologic malignancy reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Allogeneic Transplant for CMML.Current hematologic malignancy reports · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
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

1 author at 1 institution in 1 country.

Francesco OnidaUniversity of Milan - Dept. of Oncology and Hemato-Oncology Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico - Hematology/BMT Unit, Via Francesco Sforza no.35, 20122, Milan, Italy. francesco.onida@unimi.it.
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewWithin the group of the myelodysplastic/myeloproliferative overlap neoplasms of the adult age, chronic myelomonocytic leukemia (CMML) is characterized by an extremely variable clinical course. This review aims to cover over the years main advancements in the identification of CMML clinical and biological features associated to survival outcomes and the consequent development of prognostic tools for individual patient treatment decision making. RECENT

findingsAccording to the last WHO classification of myeloid neoplasms, three subgroups of patients may be recognized on the base of percentage of blasts in marrow and in peripheral blood (CMML-0, CMML-1, and CMML-2), with corresponding decreasing life-expectations. Nonetheless, in each of the subgroups, prominent disparateness of biological characteristics associates to a large heterogeneity of clinical presentation, with very different prognostic implications. Recent findings indicate that the integration of clinical and molecular data appears to provide the most helpful prognostic information. Together with an orderly enlightenment for the increasing conception of specific disease characteristics, this review offers a comprehensive and thoughtful summary of the prognostic models developed over the last three decades for CMML.

Indexed as

FemaleHumansLeukemia, Myelomonocytic, ChronicMalePrognosisSurvival RateChronic myelomonocytic leukemiaClassificationCMMLDiagnosisMDS/MPNPrognosisPrognosticationPrognostic modelRisk stratificationSubclassification

Identifiers

PMID29064026
OpenAlexW2767082237

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.