Anal Adenocarcinoma Treated in the Era of Total Neoadjuvant Therapy and Nonoperative Management.

BACKGROUND: Anal adenocarcinoma bears a treatment strategy unique to other anal cancers. OBJECTIVE: This study aimed to describe oncologic outcomes of total neoadjuvant therapy followed by watch-and-wait approach for anal adenocarcinoma. DESIGN: Retrospective analysis. SETTINGS: This study was conducted at a comprehensive cancer center. PATIENTS: Patients with anal adenocarcinoma treated between 2004 and 2019 were selected. INTERVENTIONS: Fifty-four patients received neoadjuvant therapy and were divided into 2 groups according to their treatment strategy: total neoadjuvant therapy versus single neoadjuvant modality therapy. MAIN OUTCOME MEASURES: Organ preservation, tumor regrowth, local failure, distant metastasis rates, recurrence-free survival, and overall survival. RESULTS: This study included 70 patients with anal adenocarcinoma. Fifty-four patients (77%) received neoadjuvant therapy, of whom 30 (42%) received total neoadjuvant therapy and 24 (34%) received single neoadjuvant modality. Twenty-three (33%) patients achieved complete clinical response and were managed by watch-and-wait approach. The proportion of patients able to continue to watch-and-wait approach was higher after receiving total neoadjuvant therapy (60%) compared with single neoadjuvant modality therapy (20%; p = 0.004). A tumor regrowth rate of 22% was observed in the total neoadjuvant therapy group. The 5-year overall survival rate was 70% (95% CI, 59%-83%), including 61% (95% CI, 42%-88%) for the total neoadjuvant therapy and 65% (95% CI, 48%-88%) for the single neoadjuvant modality groups. Colostomy was avoided in 50% of patients who received total neoadjuvant therapy and 83% of watch-and-wait patients. Five-year recurrence-free survival rates of 55% (95% CI, 39%-79%) and 30% (95% CI, 15%-58%) were observed in the total neoadjuvant therapy and single neoadjuvant modality groups. LIMITATIONS: Retrospective nature. CONCLUSIONS: This is the first report in the literature describing the safety and feasibility of nonoperative management for anal adenocarcinoma. Anal adenocarcinoma treated with total neoadjuvant therapy and nonoperative management achieve regrowth rates comparable to those observed in rectal cancer, with oncologic outcomes similar to those of traditional treatment strategies. See Video Abstract . ADENOCARCINOMA ANAL TRATADO EN LA ERA DE LA TERAPIA NEOADYUVANTE TOTAL Y EL TRATAMIENTO NO QUIRRGICO: ANTECEDENTES:El adenocarcinoma anal conlleva una estrategia de tratamiento único para otros cánceres anales.OBJETIVO:Describir los resultados oncológicos de la terapia neoadyuvante total seguida de observar y esperar en adenocarcinoma anal.DISEÑO:Análisis retrospectivo.AJUSTE:Este estudio se llevó a cabo en un centro oncológico integral.PACIENTES:Se seleccionaron pacientes con adenocarcinoma anal tratados entre 2004-2019.INTERVENCIONES:Cincuenta y cuatro pacientes recibieron terapia neoadyuvante y se dividieron en dos grupos según su estrategia de tratamiento: terapia neoadyuvante total versus terapia de modalidad neoadyuvante única.PRINCIPALES MEDIDAS DE RESULTADO:Preservación de órganos, recurrencia tumoral, falla local, tasas de metástasis a distancia, libre de recurrencia y supervivencia general.RESULTADOS:El estudio incluyó a 70 pacientes con adenocarcinoma anal. Cincuenta y cuatro pacientes (77%) recibieron terapia neoadyuvante, de los cuales 30 (42%) recibieron terapia neoadyuvante total y 24 (34%) recibieron modalidad neoadyuvante única. Veintitrés (33%) pacientes presentaron una respuesta clínica completa y fueron tratados con vigilancia y espera. La proporción de pacientes capaces de continuar en observar y esperar fue mayor después de recibir terapia neoadyuvante total (60%) en comparación con la terapia de modalidad neoadyuvante única (20%) ( p = 0,004). Se observó una tasa de recurrencia tumoral del 22% en el grupo de terapia neoadyuvante total. La tasa de supervivencia general a 5 años fue del 70% (IC95% 59%-83 %), incluido el 61% (IC95% 42%-88%) para la terapia neoadyuvante total y el 65% (IC95% 48%-88%) para grupos de modalidad neoadyuvante única. Se evitó la colostomía en el 50% de los pacientes que recibieron terapia neoadyuvante total y el 83% de los pacientes en observar y esperar. Se observaron tasas de supervivencia libre de recurrencia a cinco años del 55% (IC95% 39%-79%) y del 30% (IC95% 15%-58%) en los grupos de terapia neoadyuvante total y modalidad neoadyuvante única, respectivamente.LIMITACIONES:Diseño retrospectivo.CONCLUSIONES:Este es el primer informe en la literatura que describe la seguridad y viabilidad del tratamiento no quirúrgico del adenocarcinoma anal. El adenocarcinoma anal tratado con terapia neoadyuvante total y manejo no quirúrgico logra tasas de recurrencia comparables a las observadas en el cáncer de recto, con resultados oncológicos similares a las estrategias de tratamientos tradicionales. (Traducción-Dr. Fidel Ruiz Healy ).

Impact of variants of concern on SARS-CoV-2 viral dynamics in non-human primates.

The impact of variants of concern (VoC) on SARS-CoV-2 viral dynamics remains poorly understood and essentially relies on observational studies subject to various sorts of biases. In contrast, experimental models of infection constitute a powerful model to perform controlled comparisons of the viral dynamics observed with VoC and better quantify how VoC escape from the immune response. Here we used molecular and infectious viral load of 78 cynomolgus macaques to characterize in detail the effects of VoC on viral dynamics. We first developed a mathematical model that recapitulate the observed dynamics, and we found that the best model describing the data assumed a rapid antigen-dependent stimulation of the immune response leading to a rapid reduction of viral infectivity. When compared with the historical variant, all VoC except beta were associated with an escape from this immune response, and this effect was particularly sensitive for delta and omicron variant (p<10-6 for both). Interestingly, delta variant was associated with a 1.8-fold increased viral production rate (p = 0.046), while conversely omicron variant was associated with a 14-fold reduction in viral production rate (p<10-6). During a natural infection, our models predict that delta variant is associated with a higher peak viral RNA than omicron variant (7.6 log10 copies/mL 95% CI 6.8-8 for delta; 5.6 log10 copies/mL 95% CI 4.8-6.3 for omicron) while having similar peak infectious titers (3.7 log10 PFU/mL 95% CI 2.4-4.6 for delta; 2.8 log10 PFU/mL 95% CI 1.9-3.8 for omicron). These results provide a detailed picture of the effects of VoC on total and infectious viral load and may help understand some differences observed in the patterns of viral transmission of these viruses.

Nonlinear multilevel joint model for individual lesion kinetics and survival to characterize intra-individual heterogeneity in patients with advanced cancer.

In advanced cancer patients, tumor burden is calculated using the sum of the longest diameters (SLD) of the target lesions, a measure that lumps all lesions together and ignores intra-patient heterogeneity. Here, we used a rich dataset of 342 metastatic bladder cancer patients treated with a novel immunotherapy agent to develop a Bayesian multilevel joint model that can quantify heterogeneity in lesion dynamics and measure their impact on survival. Using a nonlinear model of tumor growth inhibition, we estimated that dynamics differed greatly among lesions, and inter-lesion variability accounted for 21% and 28% of the total variance in tumor shrinkage and treatment effect duration, respectively. Next, we investigated the impact of individual lesion dynamics on survival. Lesions located in the liver and in the bladder had twice as much impact on the instantaneous risk of death compared to those located in the lung or the lymph nodes. Finally, we evaluated the utility of individual lesion follow-up for dynamic predictions. Consistent with results at the population level, the individual lesion model outperformed a model relying only on SLD, especially at early landmark times and in patients with liver or bladder target lesions. Our results show that an individual lesion model can characterize the heterogeneity in tumor dynamics and its impact on survival in advanced cancer patients.

Assessing the Increased Variability in Individual Lesion Kinetics During Immunotherapy: Does It Exist, and Does It Matter?

PURPOSE: Several studies have raised the hypothesis that immunotherapy may exacerbate the variability in individual lesions, increasing the risk of observing divergent kinetic profiles within the same patient. This questions the use of the sum of the longest diameter to follow the response to immunotherapy. Here, we aimed to study this hypothesis by developing a model that estimates the different sources of variability in lesion kinetics, and we used this model to evaluate the impact of this variability on survival. METHODS: We relied on a semimechanistic model to follow the nonlinear kinetics of lesions and their impact on the risk of death, adjusted on organ location. The model incorporated two levels of random effects to characterize both between- and within-patient variability in response to treatment. The model was estimated on 900 patients from a phase III randomized trial evaluating programmed death-ligand 1 checkpoint inhibitor atezolizumab versus chemotherapy in patients with second-line metastatic urothelial carcinoma (IMvigor211). RESULTS: The within-patient variability in the four parameters that characterize individual lesion kinetics represented between 12% and 78% of the total variability during chemotherapy. Similar results were obtained during atezolizumab, except for the durability of the treatment effects, for which the within-patient variability was markedly larger than during chemotherapy (40% v 12%, respectively). Accordingly, the occurrence of divergent profile consistently increased over time in patients treated with atezolizumab and was equal to about 20% after 1 year of treatment. Finally, we show that accounting for the within-patient variability provided a better prediction of most at-risk patients than a model relying solely on the sum of the longest diameter. CONCLUSION: Within-patient variability provides valuable information for the assessment of treatment efficacy and the detection of at-risk patients.

Modelling the association between biomarkers and clinical outcome: An introduction to nonlinear joint models.

Nonlinear joint models are a powerful tool to precisely analyse the association between a nonlinear biomarker and a time-to-event process, such as death. Here, we review the main methodological techniques required to build these models and to make inferences and predictions. We describe the main clinical applications and discuss the future developments of such models.

Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.

The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 1010 copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.

Bayesian inference using Hamiltonian Monte-Carlo algorithm for nonlinear joint modeling in the context of cancer immunotherapy.

Treatment evaluation in advanced cancer mainly relies on overall survival and tumor size dynamics. Both markers and their association can be simultaneously analyzed by using joint models, and these approaches are supported by many softwares or packages. However, these approaches are essentially limited to linear models for the longitudinal part, which limit their biological interpretation. More biological models of tumor dynamics can be obtained by using nonlinear models, but they are limited by the fact that parameter identifiability require rich dataset. In that context Bayesian approaches are particularly suited to incorporate the biological knowledge and increase the information available, but they are limited by the high computing cost of Monte-Carlo by Markov Chains algorithms. Here, we aimed to assess the performances of the Hamiltonian Monte-Carlo (HMC) algorithm implemented in Stan for inference in a nonlinear joint model. The method was validated on simulated data where HMC provided proper posterior distributions and credibility intervals in a reasonable computational time. Then the association between tumor size dynamics and survival was assessed in patients with advanced or metastatic bladder cancer treated with atezolizumab, an immunotherapy agent. HMC confirmed limited sensitivity to prior distributions. A cross-validation approach was developed and identified the current slope of tumor size dynamics as the most relevant driver of survival. In summary, HMC is an efficient approach to perform nonlinear joint models in a Bayesian framework, and opens the way for the use of nonlinear models to characterize both the rapid dynamics and the intersubject variability observed during cancer immunotherapy treatment.

Longitudinal analysis of organ-specific tumor lesion sizes in metastatic colorectal cancer patients receiving first line standard chemotherapy in combination with anti-angiogenic treatment.

The purpose of this work is to assess the heterogeneity across organs of response to treatment in metastatic colorectal patient based on longitudinal individual target lesion diameters (ILD) in comparison to sum of tumor lesion diameters (SLD). Data were from the McCAVE trial, in which 189 previously untreated patients with metastatic colorectal carcinoma (mCRC) received either bevacizumab (control, C) or vanucizumab (experimental, E), on top of standard chemotherapy. Bayesian hierarchical longitudinal non-linear mixed effect models were fitted to the data using Hamilton Monte Carlo algorithm to characterize the time dynamics of the tumor burden, and to obtain estimates of the tumor shrinkage and regrowth rates. The ILD model brought more nuanced results than to the SLD model. Besides substantial differences in tumor size at baseline (with lesions located in liver more than twice as large as the ones in lungs), it revealed a more durable response in lesions located in lymph nodes and 'other organs' compared to liver and lungs. Specifically, in lymph nodes and 'other organs', the projected time to nadir was doubled in group E (2.12 and 2.44 years respectively) compared to group C (1.07 and 1.20 years respectively). This long period of tumor shrinkage associated with a slightly larger change from baseline at nadir (- 51.4% in lymph nodes and - 62.6% in 'other organs' in the group E, compared to - 46.2% and - 46.9% in group C) resulted in a clinically meaningful difference in the tumor dynamics of patients in group E compared to the group C. The proportion of variance explained by the inter-lesion variability for each model parameter was large (ranging between 10 and 56%), reflecting the heterogeneity in tumor dynamics across organs. These findings suggest that there is value in understanding both within- and between-patient variability in tumor size's time dynamics using an appropriate modeling framework, as this information may help in pairing the right treatment with individual patient profile.

Association Between Tumor Size Kinetics and Survival in Patients With Urothelial Carcinoma Treated With Atezolizumab: Implication for Patient Follow-Up.

We characterized the association between tumor size kinetics and survival in patients with advanced urothelial carcinoma treated with atezolizumab (anti-programmed death-ligand 1, Tecentriq) using a joint model. The model, developed on data from 309 patients of a phase II clinical trial, identified the time-to-tumor growth and the instantaneous changes in tumor size as the best on-treatment predictors of survival. On the validation dataset containing data from 457 patients from a phase III study, the model predicted individual survival probability using 3-month or 6-month tumor size follow-up data with an area under the receptor-occupancy curve between 0.75 and 0.84, as compared with values comprised between 0.62 and 0.75 when the model included only information available at treatment initiation. Including tumor size kinetics in a relevant statistical framework improves the prediction of survival probability during immunotherapy treatment and may be useful to identify most-at-risk patients in "real-time."