We foster dialogue between data scientists and researchers in clinics and laboratories in order to drive excellence in health care research at Stanford.
About the Data Studio
The Data Studio is a collaboration between Spectrum (The Stanford Center for Clinical and Translational Research and Education) and the Department of Biomedical Data Science. The Data Studio is open to the Stanford community engaged in biomedical research. We expect it to have educational value for students and postdocs interested in biomedical data science. The Data Studio features DBDS faculty and staff who offer the following services: workshops, office hours, and one-to-one consultations. When you complete the Data Studio request form, our coordinator and consultants will work with you to choose the right service for your research project. Appointments may be requested by completing the required form.
Workshops are an extensive and in-depth consultation for a Medical School researcher based on research questions, data, statistical models, and other material prepared by the researcher with the aid of our facilitator. During the Data Studio Workshop, the researcher explains the project, goals, and needs. Experts in the related topic from across campus will be invited and contribute to the brainstorming. After the meeting, the facilitator will follow up, helping with immediate action items and summary of the discussion. Ultimately, we strive to pair each PI with a data scientist for long-term collaboration.Office Hours are brief consultations for Medical School researchers during the last session of each month. DBDS faculty are available to advise about your research questions. Consult the schedule below to complete the Office Hour registration form. Once you have registered, you will receive a calendar invitation with the date, time, and location of the session. Bring any data, prior analyses, or other materials that you have. Our consultants may even recommend your project for a Workshop if it is appropriate.
One-to-one consultations for Medical School researchers are available year-round. Our facilitator assigns each request to a data scientist with the relevant expertise.
Partners
General questions about statistical issues may be brought to the STAT390 Consulting Workshop. This is a class offered by the Department of Statistics during each academic quarter that is staffed by graduate students and directed by a faculty instructor. The service typically consists of a single meeting with the researcher to address a specific concern, such as planning of experiments and data analysis. For more information, consult the STAT390 Consulting Workshop web page.
Researchers who are members of the Stanford Cancer Institute (SCI) conducting research projects related to cancer may request assistance from the SCI Biostatistics Shared Resource.
The Genetics Bioinformatics Service Center (GBSC) offers an end-to-end bioinformatics consulting service (BaaS) that provides high performance computational infrastructure and cutting-edge bioinformatics services for the Stanford community. The team consults on genomics, transcriptomics, proteomics, epigenetics, and metabolomics projects, and also develop custom workflows. For consulting and hands-on bioinformatics help with your projects please reach out to gbsc-baas-team@lists.stanford.edu to set up an initial meeting.
Schedule
The Data Studio is held each Wednesday from 3:00 until 4:30 pm during the fall, winter, and spring quarters of the academic year. Consult the schedule below for the location of each session. Students may participate by enrolling in BMDS 291 for an introduction to the art of statistical consultation and practicum working on projects with a biomedical researcher. All are welcome to attend. Click here to sign up for our mailing list.
The currently scheduled topic is listed below.
TITLE: Immediate vs Delayed Neuromodulation with Stereotactic Radiosurgery to the Pituitary for Refractory Oncologic Pain (INSPiRe)
INVESTIGATORS:
Scott Soltys (1)
Elham Rahimy (1)
Scott Jackson (1)
- Department of Radiation Oncology
DATE: Wednesday, 29 April 2026
TIME: 3:00–4:30 PM
LOCATION: Room R358, Edwards Building, 300 Pasteur Drive, Stanford, CA
WEBPAGE: https://dbds.stanford.edu/data-studio/
ABSTRACT
The Data Studio Workshop brings together a biomedical investigator with a group of experts for an in-depth session to solicit advice about statistical and study design issues that arise while planning or conducting a research project. This week, the investigator(s) will discuss the following project with the group.
INTRODUCTION
Control of medically refractory cancer pain is an unmet need affecting almost two-thirds of advanced stage cancer patients. Many patients require opiates, to which they can develop tolerance and require higher doses, with problematic side effects including nausea, constipation, and sedation. Ablation/modulation of the pituitary via different techniques (surgical, chemical, and more recently with radiotherapy) has demonstrated significant and fast pain relief in non-randomized studies dating back to the 1950s. There is a need for a randomized trial to evaluate the efficacy and safety of pituitary SRS for refractory cancer pain. A sham-arm is needed for comparison given the known enhanced placebo-effect of procedural treatments, including radiotherapy.
HISTORICAL DATA
As summarized in Table 1, rapid, clinically significant pain relief is expected in these patients with cancer pain otherwise refractory to current management. With reduction in opioid dose and side effects, quality of life would be expected to improve.
STUDY POPULATION
Patients with incurable cancer with refractory moderate/severe cancer pain, defined as pain score of 6–10 on the Brief Pain Inventory for ‘average pain in the last 24 hours’ or 4–10 with a morphine equivalent dose (MED) > 100mg per day
STUDY DESIGN
Randomized Phase II, single-blind, sham-controlled, uni-directional cross-over trial.
Study Intervention: Stereotactic RadioSurgery (SRS) to the pituitary, immediate 160 Gy Dmax versus sham of 0 Gy, with cross-over to treatment for sham non-responders.
Patients will be randomized to SRS or a sham treatment in which no radiation is delivered.
Patients without a pain-response at 14 days post-treatment in the sham group may cross-over to the SRS arm and receive treatment on day 15 (up to day 21).
Sample Size: 24 total patients (12 patients per arm)
Number of Sites: Single institution
Study Duration: 36 months with estimated accrual of 8 patients per year.
Participant Duration: 24 months or until time of death.
HYPOTHESIS & OBJECTIVES
We hypothesize that pituitary SRS is associated with meaningful pain improvement at 2 weeks compared to sham-treatment. The Primary objective is to determine whether pituitary SRS is associated with improved pain response at 14 +/- 2 days post-SRS compared to sham treatment, using International Consensus on Palliative Radiotherapy Endpoints (ICPRE) definition of pain response. There are five secondary objectives. First is to determine whether pituitary SRS is associated with improved pain response at 14 +/- 2 days post-SRS compared to baseline, using other definitions of pain response: (percentage >30% pain score reduction, or substantial pain response >4-point pain score reduction or percentage >50% pain score reduction). Second is to determine whether pituitary SRS is associated with improved Patient Global Impression of Change (PGIC) on day 14+/-2 days. Third is to determine whether pituitary SRS is associated with improved quality of life through the European Organization for Research and Treatment of Cancer (EORTC) quality of life questionnaire core-30 (QLQ-C30) and brain cancer specific module (QLQ-BN20), quality-adjusted life year (QALY) through the EuroQol (EQ)-5D questionnaire, and caregiver quality of life through the Caregiver Quality of Life Index-Cancer (CQOLC) scale. Fourth is to determine the median overall survival following pituitary SRS. Fifth is to determine if pain response is associated with improved overall survival compared to patients without a pain response.
ENDPOINTS
The primary endpoint is Pain response (complete and partial responses) at 14 +/- 2 days post-SRS compared to baseline, using ICPRE definitions. There are multiple secondary endpoints:
Pain evaluated daily with BPI-SF (short form) on days 1–7 (treatment is day 0), day 10 +/- 2 days, day 14 +/- 2 days, weekly for 2 months, then monthly
Pain response at day 14+/-2 days with >30% pain score reduction
Pain response at day 14+/-2 days with >50% pain score reduction
Pain response at day 14+/-2 days with >4-point pain score reduction
Patients’ Global Impression of Change (PGIC) Score on day 14+/-2 days
EORTC QLQ-C30 and QLQ-BN20
QALY through the EQ-5D questionnaire
CQOLC scale
Overall survival of three patient subgroups: 1) initially randomized to 0 Gy versus 160 Gy; 2) who ultimately received 160 Gy versus 0 Gy; 3) with pain response versus those without pain response
STATISTICAL PLAN
Sample size was calculated for the primary endpoint (pain response at 14 days between sham versus SRS arms) using an expected response rate of 80% in the SRS arm, 20% in the sham arm, 2-sided alpha of 0.05, and beta of 0.2 (power of 80%). This calculation yielded a requirement of at least 10 patients per arm. Assuming 10% dropout, 12 patients per arm are required. If dropout rate exceeds 10%, additional patients will be accrued upon approval.
STATISTICAL QUESTIONS
- Is this correct/ideal under Study Design: “Permutation with random block sizes will be used for treatment assignments to balance the stratification variables of histology (breast/prostate versus other) and pain type (nociceptive-somatic versus nociceptive-visceral and mixed nociceptive/neuropathic). The randomization list will be developed and uploaded to RedCap.”
- Is this correct/ideal under Study Population: “Only patients that receive initial SRS or sham SRS will be considered evaluable for safety and efficacy endpoints. Unevaluable patients may be replaced by additional participants.”
- Ying’s comment: “The language of replacement of evaluable participants makes sense for patients who are randomized but never receive study treatments. I am not sure about non-evaluable status for early drop-off patients. Once a patient received treatment, they are in the ITT population. Because you evaluate pain daily, you may be able to impute pain status even if they drop out earlier. We will need a missing data strategy to handle missing data in the final analysis.”
- Our question: How do we approach this? What should we write for the missing data strategy?
- Is this correct/ideal under Analysis Plan: “For patients who are not evaluable for pain response at Day 14 (+/- 2 days), their response status will be imputed. The patient requires at least one baseline pain score and at least one pain score from days 5–16 to be evaluable. The response rates will be listed as percentages with 95% confidence intervals for each arm. Relative response rate and odds ratio will be estimated with 95% confidence intervals. Statistical inference for comparing pain response between pituitary SRS and sham groups will utilize a Fisher’s exact test. Sensitivity analysis can be done to analyze cross-over data to see if the results are consistent in the direction for a McNemar test. Of note, the study is not powered by cross-over.”
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