Evidence map›Paper›PMID 34276915›Full record

ReviewMediterranean journal of hematology and infectious diseases2021

Systemic Mastocytosis: Molecular Landscape and Implications for Treatment.

Cecilia Monaldi, Sara De Santis, Manuela Mancini, Samantha Bruno, Michele Cavo, Simona Soverini

Abstract readReview
In one paragraph

Review in Mediterranean journal of hematology and infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Systemic Mastocytosis: Multidisciplinary Approach.Mediterranean journal of hematology and infectious diseases · 2021
    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

6 authors.

Cecilia MonaldiDipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.
Sara De SantisDipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.
Manuela ManciniIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", Bologna, Italy.
Samantha BrunoDipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.
Michele CavoDipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.
Simona SoveriniDipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past decade, we have witnessed significant advances in the molecular characterization of systemic mastocytosis (SM). This has provided important information for a better understanding of the pathogenesis of the disease but has also practically impacted the way we diagnose and manage it. Advances in molecular testing have run in parallel with advances in therapeutic targeting of constitutive active KIT, the major driver of the disease. Therefore, assessing the molecular landscape in each SM patient is essential for diagnosis, prognosis, treatment, and therapeutic efficacy monitoring. This is facilitated by the routine availability of novel technologies like digital PCR and NGS. This review aims to summarize the pathogenesis of the disease, discuss the value of molecular diagnostic testing and how it should be performed, and provide an overview of present and future therapeutic concepts based on fine molecular characterization of SM patients.

Indexed as

Allele burdenKITSystemic mastocytosisTyrosine kinase inhibitor

Identifiers

PMID34276915
PMCPMC8265368

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.