Joint model with latent disease age: Overcoming the need for reference time

Heterogeneity of the progression of neurodegenerative diseases is one of the main challenges faced in developing therapies. Thanks to the increasing number of clinical databases, progression models have allowed a better understanding of this heterogeneity. Joint models have proven their effectiveness by combining longitudinal and survival data. Nevertheless, they require a reference time, which is ill-defined for neurodegenerative diseases, where biological underlying processes start before the first symptoms. In this work, we propose a joint non-linear mixed-effect model with a latent disease age, to overcome this need for a precise reference time. We used a longitudinal model with a latent disease age as a longitudinal sub-model. We associated it with a survival sub-model that estimates a Weibull distribution from the latent disease age. We validated our model on simulated data and benchmarked it with a state-of-the-art joint model on data from patients with Amyotrophic Lateral Sclerosis (ALS). Finally, we showed how the model could be used to describe ALS heterogeneity. Our model got significantly better results than the state-of-the-art joint model for absolute bias on ALS functional rating scale revised score (4.21(SD 4.41) versus 4.24(SD 4.14)(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>p</mml:mi></mml:math>-value<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>=</mml:mo></mml:math>1.4<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>17</mml:mn></mml:mrow></mml:msup></mml:math>)), and mean-cumulative-AUC for right-censored events on death (0.67(0.07) versus 0.61(0.09)(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>p</mml:mi></mml:math>-value<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>=</mml:mo></mml:math>1.7<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>03</mml:mn></mml:mrow></mml:msup></mml:math>)). To conclude, we propose a new model better suited in the context of unreliable reference time.

Institutions

Publication Details

Journal
Statistical Methods in Medical Research
Published
2026-01-02
DOI
https://doi.org/10.1177/09622802251399917
Primary Topic
Bone and Joint Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Joint model with latent disease age: Overcoming the need for reference time

Statistical Methods in Medical Research
Bone and Joint Diseases
article

Joint model with latent disease age: Overcoming the need for reference time

article en

Abstract

Heterogeneity of the progression of neurodegenerative diseases is one of the main challenges faced in developing therapies. Thanks to the increasing number of clinical databases, progression models have allowed a better understanding of this heterogeneity. Joint models have proven their effectiveness by combining longitudinal and survival data. Nevertheless, they require a reference time, which is ill-defined for neurodegenerative diseases, where biological underlying processes start before the first symptoms. In this work, we propose a joint non-linear mixed-effect model with a latent disease age, to overcome this need for a precise reference time. We used a longitudinal model with a latent disease age as a longitudinal sub-model. We associated it with a survival sub-model that estimates a Weibull distribution from the latent disease age. We validated our model on simulated data and benchmarked it with a state-of-the-art joint model on data from patients with Amyotrophic Lateral Sclerosis (ALS). Finally, we showed how the model could be used to describe ALS heterogeneity. Our model got significantly better results than the state-of-the-art joint model for absolute bias on ALS functional rating scale revised score (4.21(SD 4.41) versus 4.24(SD 4.14)(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>p</mml:mi></mml:math>-value<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>=</mml:mo></mml:math>1.4<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>17</mml:mn></mml:mrow></mml:msup></mml:math>)), and mean-cumulative-AUC for right-censored events on death (0.67(0.07) versus 0.61(0.09)(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>p</mml:mi></mml:math>-value<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>=</mml:mo></mml:math>1.7<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>03</mml:mn></mml:mrow></mml:msup></mml:math>)). To conclude, we propose a new model better suited in the context of unreliable reference time.

Statistical Methods in Medical Research
Centre National de la Recherche Scientifique (FR), Inserm (FR), Sorbonne Université (FR), Assistance Publique – Hôpitaux de Paris (FR), Institut du Cerveau (FR)
Openalex Percentile: Top 100%
Bone and Joint Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.