SynthesisClinical drug investigation2016
First-Line Treatments for Poor-Prognosis Metastatic Renal Cell Carcinoma: Experts' Prescribing Practices and Systematic Literature Review.
Synthesis in Clinical drug investigation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Pooled it
- A three miRNAs panel in paraffin tissue serves as tool for predicting prognosis of renal cell carcinoma.Frontiers in oncology · 2024Article
- Transient Receptor Potential Channel 1 Potentially Serves as a Biomarker Indicating T/TNM Stages and Predicting Long-Term Prognosis in Patients With Renal Cell Carcinoma.Frontiers in surgery · 2022Article
- The Current and Evolving Landscape of First-Line Treatments for Advanced Renal Cell Carcinoma.The oncologist · 2019Review
- Overexpression of cannabinoid receptor 1 promotes renal cell carcinoma progression.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesNo head-to-head clinical trials are available to help physicians in the decision-making process of first-line therapy in poor-prognosis metastatic renal cell carcinoma (RCC). The objectives of our study were to identify experts' prescribing practices and to review available clinical data in first-line therapies for poor-prognosis metastatic RCC (mRCC).
methodsThirteen RCC experts were asked to fill in a self-administered questionnaire evaluating prescribing practices. A systematic review was performed in July 2015 in MEDLINE for clinical trials evaluating first-line strategy in poor-prognosis mRCC.
resultsTen out of 13 experts completed the questionnaire (76.9%). Sunitinib was the most frequently prescribed first-line therapy (8/10; 80%). The main reason for prescribing sunitinib most frequently was the evidence of effectiveness for the majority (5/8 experts). A total of 21 articles were found suitable. Only one phase III randomized controlled trial in which all patients had a poor prognosis was retrieved. Temsirolimus increases progression-free survival and overall survival compared to IFN-alpha. Increased PFS with sunitinib in poor-prognosis patients was shown in a subgroup analysis of the pivotal trial. An expanded-access trial confirmed this result. DISCUSSION: Experts tend to prefer sunitinib as first-line therapy even in poor-prognosis mRCC. In light of the systematic review, no targeted therapy appears to be more effective than another. The upcoming challenge is to discover more effective new drugs since the overall survival of poor-prognosis mRCC still remains extremely limited.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.