Development and External Validation of Integrated Machine Learning-Based Prognostic Model in Oropharyngeal Head and Neck Cancer Using the Systemic Inflammatory Response Index.

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

1 citing paper in PubMed.

1. Toward personalized prediction: a multicenter machine learning model for omalizumab response duration in moderate-to-severe perennial allergic rhinitis.Frontiers in allergy · 2026
   Article

Corrections and comments

• Update of
  An integrated machine learning-based prognostic model in head and neck cancer using the systemic inflammatory response index and correlations with patient reported financial toxicity.2025

Authors and funding

20 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

Indexed as