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WO2002051354A2 - Systeme et procede d'elaboration de medicaments destines a une utilisation selective de medicaments chez des individus, patients repondant au traitement et applications du procede dans des soins medicaux - Google Patents

Systeme et procede d'elaboration de medicaments destines a une utilisation selective de medicaments chez des individus, patients repondant au traitement et applications du procede dans des soins medicaux Download PDF

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WO2002051354A2
WO2002051354A2 PCT/US2001/049457 US0149457W WO02051354A2 WO 2002051354 A2 WO2002051354 A2 WO 2002051354A2 US 0149457 W US0149457 W US 0149457W WO 02051354 A2 WO02051354 A2 WO 02051354A2
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patient
treatment
clinical
drug
patients
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WO2002051354A3 (fr
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Robert E. Becker
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/032—Transmission computed tomography [CT]
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Definitions

  • serial no. 60/258,262 filed December 26, 2000, entitled “Method of Administering ChEIs for treating Alzheimer' s Disease”
  • serial no. 60/274,981 filed March 12, 2001, entitled “Method of Drug Development for Selective Use with Individual, Treatment Responsive, Patients”
  • serial no. 60/301,526, filed June 28, 2001 entitled “Method of Drug Development for Selective Use with Individual, Treatment Responsive, Patients and the Applications of the Method of Drug Development in Medical Care”.
  • the present invention relates to systems and methods that use randomized assigned subjects in double-blind, placebo-controlled, clinical trials ("CTs") or other medical research designs to evidence support for strong hypotheses that predict the efficacy and safety of drugs, medical interventions, procedures, treatments or devices (hereafter collectively referred to as "treatments” or “drugs”) or other treatments in individual patients.
  • CTs clinical trials
  • the present invention differs from current practice in that current CT and clinical research evidence support for weak hypotheses by determining the efficacy and safety ofa treatment for a group of treated patients.
  • CT or research extended with the methods of the invention on the other hand, evidence support for strong hypotheses by determining efficacy and safety of a treatment selectively among individual patients.
  • the clinician does not have scientific validations that the CT average randomized patient resembles her individual patient in all ways important to successful treatment; that her clinical methods of assessment have sufficient reliability and validity (e.g., are sufficiently free from random or systematic error from one administration to another and express the actual condition of the patient or the true clinical course of the patient) to be grounds for clinical judgments about the patient's response to the therapeutic intervention; that the criteria of clinical significance she selects reflect the current standard of medical knowledge; in decision making that the odds for efficacy and safety for the mean patient in the group apply to her individual patient; and so forth.
  • the evidence currently available from clinical trials has been severely criticized for being insensitive to "clinical nuances" that are crucial considerations in patient care. (Feinstein and Horwitz, 1998). In contrast to these limitations in current clinical trial practice, it would be desirable to develop a system and method that use CT research: I. To implement as the aims of CT investigation to evidence treatment effects reliably and validly in individual patients.
  • D. Select the reference that determines the probability of a treated patient's response in one treatment arm being dependent on the treatment in that condition.
  • E. Defend the internal validity of both the double-blind, placebo-controlled and the post-double-blind, placebo-controlled open periods of the CT.
  • CTs do not characterize individually the different courses taken by different patients when they compare groups in treatment arms. Statistical significance for the presence of a difference among groups is not evidence of clinical significance of a treatment for individual patients.
  • n-of-1 trial provides one resource when randomized controlled trials do "not help in deciding treatment for an individual patient.” (Drug Ther Bull, 1998). Accordingly, it would be desirable to make the n-of-1 trial — currently the only clinical research method believed to be valued more highly than the clinical trial — more practical and effective. (Guyatt et al., 2000).
  • the n-of-1 trial has limitations: the randomization procedure is time consuming; the trial exposes the patient to periods of no treatment in placebo treatment; and the trial often has less statistical power than a CT, increasing the likelihood of erroneously continuing or discontinuing a treatment on the basis of the n-of-1 trial results, or the results being inconclusive. Therefore, the clinician frequently will not want to use the n-of-1 trial technique when its use can be avoided.
  • Evidence-based medicine currently embodies the modern standards for patient care.
  • Evidence-based medicine (“EBM”) "acknowledges that intuition, unsystematic clinical experience, and pathophysiologic rationale are insufficient grounds for clinical decision making, and stresses the examination of evidence from clinical research.” (Guyatt et al., 2000, p. 1291).
  • CTs or "randomized trials” as they are sometimes called, are one of the highest standards in clinical research, in practical research, and in regulatory perspective constitute the state of the art.
  • Modern scientific medicine depends upon the quality of the research evidence.
  • the drugs are represented as more effective than justified by the variance in outcomes in the placebo groups.
  • Becker and Markwell, 2000 the authoritative reports and recommendations of experts do not address the inability of the physician to reach reliable and valid assessments of the individual patient, the effect of error in test-retest on outcome measures, and the problems these assessment deficiencies raise for scientifically and medically sound medical decision making.
  • the current methods of reporting do not take into account the inability of clinicians to assess individual patient responses.
  • the lack of recognition of this failing in current clinical methods leads to ungrounded decisions about dosing changes and clinical response.
  • clinicians are encouraged to assess the benefits from drug administration and to reach clinical judgments about dosing and management using scientifically inadequate analyses of CTs and unreliable and invalid clinical assessments. (Becker and Markwell 2000).
  • the statistical rejection of a strong null hypothesis in a CT opens to consideration a strong research hypothesis of treatment efficacy conditional on the specific conditions of the application of the drug or device to individual patients and the individual responses of patients to the treatment.
  • the system and method of the invention uses CTs to develop, test and demonstrate the use of a model decision rule or rules that can then be applied in medical practice to individual patients to reliably assess probable drug efficacy or lack of efficacy in each individual patient on an ongoing basis and to predict the probable ultimate outcome from continued treatment.
  • the system and method of the invention preferably facilitates the ongoing assessment of patients by n-of-1 studies.
  • a principal aim of the present invention is to provide the medical practitioner scientific and statistical evidence of individual patient responses to treatment.
  • the system and method of the invention develops and tests a model that assesses individual patient responses to drugs.
  • the model generated by the invention in the clinical trial provides physicians in clinical practice with a scientifically and statistically founded means to determine whether an individual patient currently benefits or not from the treatment, and the most probable outcome for each patient as an individual (i.e., immediate or ultimate clinical benefit, or treatment failure) with continued treatment of the individual patient.
  • physicians apply clinical trial evidence about drug effects in groups of patients to an individual patient using unsystematized clinical experiences and clinical judgments of the patient's responses to treatment as the grounds of individual patient medical care decisions.
  • a significant advantage of the present invention is that it may be applied in clinical drug development to provide the practicing physician with the needed, but currently unavailable resources, to apply CT evidence to individualized patient care by drawing on a research tested model that evaluates individual patient responses.
  • the system and method generates and tests a model of individual patient assessment of drug or device effects that has a wide range of applications:
  • FDA Federal Drug Administration
  • NDA National Health Organization
  • drug a device, intervention, procedure, or other treatment
  • Figure 1 is a graphical illustration of a statistical model generated by a CT in accordance with a preferred embodiment of the present invention.
  • the present invention aims to evidence treatment effects in each individual patient in a CT reliably and validly.
  • the present invention is directed to a system and method of CT, CT design, CT analysis, and CT application, or any other research, to determine the efficacy, safety, economic benefits or costs, or uses ofa drug, intervention, procedure, or medical device. It is assumed that CTs or other evaluative research that use the method of the invention incorporate current standards for CT research, including but not limited to randomized assignment of subjects to treatment arms, unbiased selection of the sample from the population eligible for the applications, double-blinding, placebo-controls, and so forth.
  • the present invention adds to current CT practice the following methods that extend CTs to identify treatment effects in individuals:
  • the aim of the pre-trial test-retest reliability studies and assessment planning is to estimate reliably the patient's true clinical course by controlling for the uncertainties introduced by measurement error or other sources of variance.
  • repeated measures must provide sufficient reliability for the scalar summary statistic to accurately express the true clinical course of each individual in the trial.
  • scalar summary statistics are bounded by the appropriate confidence interval of measurement. Analysis of co-variance or other statistical adjustments may be required in a manner known to those of ordinary skill in the pertinent art to take into account baseline, pre-treatment, or within trial effects of independent variable differences among patients or within trial effects. (Hays, 1963, p. 564; Senn, 1997, pp. 95-104).
  • the scalar summary statistics for each patient are fitted to a statistical or other model, such that the changes in status over time for each patient can be analyzed.
  • the method of the invention can be used in regression on baseline status variables to predict treatment effects in individual patients using methods of regression in a manner known to those of ordinary skill in the pertinent art.
  • assessments are used to provide the data points for the summary scalar statistic of the patient's course.
  • the assessment plan derived from the pre-trial reliability study specifies study design and analysis — how frequently outcome measures are administered to patients, how multiple administrations avoid carryover effects, and so forth, as required in assessment and measurement, and whether a descriptive statistic summarizing multiple administrations or a single occasion of administration are used in data analysis to test the hypotheses of the study and to develop the model for clinical treatment that will express the efficacy, safety, uses, or other dimensions of the treatment important to individualized patient care decisions.
  • Outcome measure reliability can be re- studied at any time during or after a CT to establish an assessment plan that meets the aims of the study or aims of a physician's application in patient care.
  • Criteria of clinical significance are derived from the current state of medical knowledge and standards of care. These criteria identify individual patients as responders or not responders to a treatment. Criteria of clinical significance designate the scalar summary statistic that summarizes each patient's clinical course as a clinically significant response or non-response to the treatment received.
  • the judgment of response or non-response can be categorical or probability based according to the conditions set by the investigators, the aims or design of the study, or current medical, statistical, or scientific standards of practice.
  • This, or other scientifically, medically, or statistically, justifiable criteria are used in the extended CT to implement the inference to an individual being a responder or not; to establish the probability that an individual's clinical course could occur under placebo or under treatment conditions; to statistically support the internal validity ofa study; to select confidence intervals; to distinguish as different two clinical courses; and so forth.
  • the criteria conditions governing specific comparisons often will be specified in relation to the aims or design requirements of the study because, as discussed under D.
  • the probabilities associated with the use of confidence intervals in judging the difference between two estimates are sensitive to the statistical characteristics of the estimates. (Schenker and Gentleman, 2001). Also, risk-benefit ratios will apply in particular instances in a manner known to those of ordinary skill in the pertinent art based on the teachings herein. For example, a relatively high probability that a specific patient's response after receiving a treatment could occur under placebo conditions in the CT can lead to different patient care decisions under different conditions. Where the risk of continued treatment is low, or the risks of discontinuing treatment if it is effective could be extremely serious for the patient, the physician may choose to continue treatment, in effect accepting as the criteria of statistical significance more than one chance in 20 of the response not being an effect of treatment.
  • researchers and clinicians will accept different probabilities, different confidence intervals, and so forth, according to customary scientific, statistical, decision making, and medical practices, and because they will balance risks and benefits in taking decisions or in inferences.
  • D. Select the reference that determines the probability of treated patient's response in one treatment condition being dependent on the treatment in that condition. After characterizing an individual under the criteria of clinical significance, the investigator and treating physician ask for a probability that a patient's response is a consequence of treatment.
  • the statistical probability of a patient's response occurring as an effect of treatment can be estimated in various comparisons: the probability that the actively treated patient's course would occur under comparison or placebo conditions; whether the confidence interval of the actively treated patient's course overlaps the mean comparison, or the mean placebo treated patient course, or its confidence intervals; as an odds ratio of the cumulative frequency of the patient's course among actively treated patients divided by the cumulative frequency among comparison or placebo treated patients; as an exact probability determined by a randomization test; and so forth.
  • the conditions of comparison of the individual patient's course to the patient courses in the clinical trial are aim and design specific, both because differences in aims and design require different comparisons, and because the statistical characteristics of the estimates, point, descriptive, summary scalar, with different variances, confidence intervals, and so forth, interact with how conservative an estimate need be in the selection of the statistical test.
  • the method of the invention is useful when a placebo group cannot be justified as a CT comparison to the treatment of interest. If a treatment is shown effective and safe for a disease with serious consequences if left untreated, the disease is progressive, and so forth, the availability of a treatment can preclude the use of placebo treatments in future CT.
  • the comparison of efficacy is not to placebo, but to criteria of clinical and statistical significance using outcome measures of demonstrated reliability to provide confidence intervals for individual patient's clinical courses.
  • Secondary support for treatment efficacy comes from the distributions of responders among treatment arms refining the equivalence CT where two active treatments are compared. Two treatments may appear equivalent, one not superior to the other because the confidence intervals for the means overlap. Nonetheless, individual patient courses may show that for some patients one treatment is superior to the other and with clinical advantages not evidenced in the group comparisons.
  • the aim of the extended clinical trial of the invention is not to evidence for the pharmacological scientist that a drug is different from placebo in the human species or in a subset of the species. Rather, the aims are to develop a decision model useful to the clinician deciding whether each patient shows an optimal clinical response and if the response is an effect of treatment.
  • One implementation of these aims may be to calculate an odds ratio for each clinical course occurring under treatment and placebo conditions.
  • the statistical testing of a distribution of patient outcomes among different levels of treatment, different treatments, or a treatment and placebo can be combined with Generalizability and Decision studies of individual patients, individual patients grouped by confidence intervals (for example, where a long-term health outcome is an aggregate derived from the surrogate outcomes for all patients with courses that fall within the confidence interval calculated for the patient of interest in the research or to a practitioner) categories of patients (such as those with outcomes that fall above and below clinical criteria oi response or in relation to different aggregated responses and confidence intervals developed out of the aims or design of the study). Extended clinical trials can also provide statistical test support for internal validity of the open or non-blind phase of the CT.
  • the currently preferred embodiment of the present invention requires first, a reliable projected estimation of placebo treated patient outcomes after the double-blind as a comparison group to establish a probability for the treated patient's status and second, evidence against bias influencing the open assessments of patients in followup.
  • Evidence from test-retest reliability studies comparing blind and open use of outcome measures, evidence demonstrating no significant effect (no effect greater than the confidence interval of measurement) on patient courses following the transition from blind to open treatment conditions, and so forth, can be generated in the CT to support the reliability of outcome measures in the hands of practitioners who establish test-retest reliability and follow the assessment plan required by the aims of treatment. Even if the CT in open extension loses internal validity, continued compliance with the reliability of measurement and criteria governing the double-blind model can support the validity of the model to indicate response and treatment dependence of response if other assumptions are met.
  • the confidence intervals of measurement determined in the CT indicate change; a placebo course that crosses the 90% confidence interval of measurement of the active treatment course evidences less than 5% chance occurrence of the difference.
  • CT outcome measures are surrogates for clinically important health outcomes: blood pressure for stroke, heart disease, kidney failure; blood glucose for blindness, kidney failure, cardiovascular disease, and so forth.
  • the method of the invention by characterizing individual courses, can generate probabilities for long-term health outcomes specific to distinct clinical responses — individual courses; course intervals bounded by confidence intervals of measurement, and so forth. The method of the invention thus more precisely equates differences among courses measured by surrogate outcome variables with different predicted long-term health effects. This can improve risk-benefit evaluations of treatment decisions.
  • H Methods of analysis. Extended clinical trial analysis draws on statistical, clinical trial, medical and other methods of analysis as needed to implement the methods of the invention.
  • the method of the invention to use the individual patient as the unit of analysis may require as an item of data for an individual patient any of the following:
  • a medical assessment at an instant in time for example, a blood pressure, a laboratory test result, a score or single response to a question or other stimulus, or any other result from a medical examination.
  • An aggregated score or response where established methods provide a questionnaire or rating scale score, a summary score or quantification of a laboratory, or imaging or other medical study of the patient.
  • a profile of the patient over time for example, a defined time period, of an hour, day, week, or other period of time, where an aggregated measure(s) over the time become the unit of repeated measurements, comparison, and analysis.
  • the methods of this invention can employ exploratory data analysis and methods of analysis known to anyone familiar with the art of drug development and statistical analysis of drug research, including but not limited to:
  • Post-hoc analysis may be appropriate in extended clinical trials. If permutation or randomization tests do not allow the investigator to reject the strong null hypothesis, clinically significant differences may still be present within each treatment arm. This possibility can be explored by determining if the placebo or control arm of the study contains a significantly different distribution of subjects on the outcome variable between pre- and post- randomization. A significantly widened distribution of placebo treated subjects' scores comparing post-randomization outcome scores to pre-randomization outcome scores can occur with a reduced reliability in the outcome measures over time, a treatment or time effect on patients in the overall study not associated with the specific arms, or a placebo specific effect that may affect patients who would not respond in other treatment arms. Any of these conditions may have clinical significance and warrant further investigation.
  • the practicing clinician uses or adapts to the individual patient situation the criteria of clinical and statistical significance from the trial to judge the response status of the patient and the probable level of confidence appropriate for the judgment of response status.
  • the extended clinical trial provides confidence intervals for measurement of outcomes from treatment, and a model for assessing each patient's clinical course in relation to established medical and statistical criteria of significance. With these resources in hand, the clinician no longer depends on weakly supported clinical judgments or distribution-based probabilities from group comparisons to manage patients using clinical trial evidence.
  • regulatory authorities approve a drug for prescription with the indication that it is to be prescribed selectively to patients who benefit.
  • the managing physician uses one or more of the research tested means of assessment to ascertain patient response and selectively use the treatment in responders and to modify treatment in those without satisfactory response.
  • the practicing physician during the course of management can employ as needed n-of-1 trials for individual patients to provide additional assessment of the benefits of treatment in the patient.
  • An n-of-1 trial can be used to confirm or disconfirm the application of the model to this individual patient. Other patients, with the passing of time may deteriorate sufficiently that the CT confirmed model judges the probability of drug induced efficacy as less than the probability of no treatment effect. Again, an n-of-1 trial can be used to assess the prediction from these probabilities.
  • the outcome of the n-of-1 trial can be fitted to the original model and probabilities of the treatment and placebo responses determined from the original model as described above. The comparative probabilities or an odds ratio can inform the physician of the likelihood of benefit from treatment in this one patient.
  • the n-of-1 trial can also be statistically analyzed within itself if the clinician prefers.
  • the method of the invention allows a Bayesian analysis using the probabilities from the patient's treatment as priors, and the probabilities from the comparison of the n-of-1 trial outcomes to the model as posteriors, in addition to the frequentist probabilities used to interpret the trial in isolation.
  • the method of the invention anticipates a CT confirmed model for the n-of-1 trial providing scientific grounding to interpretations of n-of-1 trials carried out in individual patient care. The clinician can use this method to test the efficacy of drug dosing changes, or beginning or ending dosing, prescribed in response to the clinical course of the individual patient.
  • the utility he cost- benefit ratio — of maintaining or discontinuing treatment, or the odds ratio — even odds, or clinical judgment of the physician, may call for a confirmation of the clinician's evaluation and treatment intention supported by the clinical application of the research model.
  • the clinician predicts a response to discontinuing drug, or to reinstating drug if the patient has already been discontinued.
  • the physician determines the regression slopes or means of treatment and placebo periods and applies the research model.
  • the physician takes his initial prediction as confirmed or disconfirmed with an associated probability.
  • the clinician can use other methods as discussed above.
  • the physician can confirm that an apparent responder or non-responder is or is not benefiting from the drug or device when support beyond the initial application of the research model is needed.
  • a pharmaceutical manufacturer may choose to use the method of the invention.
  • the method of the invention better defines the appropriate place of the new therapy in patient care by the ability to individualize patient care decision making. Physician, family, and patient assessments are not mistaken as indicators of outcome when in fact they reflect the errors inherent in the methods of assessment or differences in response between patients. Patients can be maintained on a medication that will most probably benefit them or discontinued from a medication with no evidence of benefit opening opportunities for alternative forms of treatment. An expensive new treatment receives wider acceptance by hospital pharmacy committees and medical care funders as an approved treatment because the costs can be better controlled with access to research that uses the method of the invention.
  • a pharmaceutical company may recognize that a further investment to re-develop an already approved drug becomes economically advantageous in the competitive marketplace because the more selective use and its advantages to patients and medical care providers will have patent protection.
  • the company may pursue a more precise regulatory approval available with the methods of the invention for its distinct advantages. Because of these advantages, the method of the invention can be used to develop a compound without patent protection because the developer could anticipate protection under the method of development.
  • a drug with high costs for each treated case because a large number of persons would have to be treated to benefit a small number can be developed with the method of the invention to target the persons who are responders and to not treat the nonresponders, thus reducing the costs per patient benefited.
  • a new treatment shows equal efficacy to an earlier more expensive treatment for a medical condition.
  • a small margin of additional mean benefit for the old treatment is disregarded by funders of medical care because of the high costs of the old treatment and the vague benefits.
  • Applying the method of the invention to a clinical research study of the old treatment identifies significant additional efficacy for about 25% of patients and shows that a practitioner's brief use of the treatment to identify responders from non- responders adds only about 20% to the cost of treatment of each benefited patient.
  • approve the old treatment used in conjunction with the method of the invention and methods applied to the new treatment are examples of the old treatment used in conjunction with the method of the invention and methods applied to the new treatment.
  • an inexpensive medication effective in some patients with a given medical condition competes with an expensive medication more generally effective and free of adverse events.
  • An organization responsible for funding medical care wishes to improve the overall quality of the care and to avoid unnecessary expenses.
  • the organization agrees with the pharmaceutical manufacturer of the more expensive product that if they will develop a model for the effective, safe, and economical, use of the inexpensive and patented medications the organization will approve both for use and reimbursement.
  • the manufacturer demonstrates how specific indicators of outcome can be followed in individual patients to identify, early in treatment, those who will reach maximum benefit on the inexpensive medication and those who will require the more expensive medication. This model becomes the standard controlling use of these medications in the medical care provided by, or reimbursed by, the funding organization.
  • the scientifically highest quality medical care is provided to patients at the lowest possible cost for such quality care.
  • D In electronic medical records. Current plans for achieving widespread use of the electronic medical record within a decade recognize the easier access, reduced confusion interpreting reference standards that differ among providers, improved control over errors, and the ability to monitor medical care for response to community needs and overall quality of treatment.
  • the electronic medical record develops out from the individual patients seen by the physician; it provides no support to making evidence-based medicine more immediately appropriate to and applicable in the care of the patient.
  • the method of the invention offers this further step ofa dynamic interaction of electronic medical records with CT evidence as a resource available to physician and patient to monitor medical treatments.
  • randomized controlled trials allow treatment decisions to take into account the specific probabilities for patient outcomes from different treatments and to monitor the progress of each patient in relation to the scientific evidence of individual patient courses and outcomes evidenced in the method of the invention randomized controlled research trials.
  • the method of the invention integrates the aims of evidence-based medicine and : electronic medical records to capitalize on these advantages by providing patient care that is scientifically and individually integrated.
  • An anxious or personally concerned patient who wishes to participate actively in her own health care explores the method of the invention modeled, randomized, controlled trials and traditional clinical trials relevant to her condition using Internet access to Medline and Medline plus.
  • the better informed patient can select among treatments that seem most soundly justified to her and more easily engage in final decision making with the physician.
  • the patient already in treatment can compare her progress with the research results in other trials.
  • the patient better understands both her progress as a predictor of ultimate outcome using the method of the invention randomized controlled trials for her treatment and the place of her treatment among the options available for a person with her condition.
  • Medical care is opened to the patient participating in the applications of scientific evidence in her care: the patient is more fully informed; the physician deals with a better educated patient without the burden of summarizing the relevant literature for the patient. Less mystified, more centrally involved, better able to reach sound preliminary scientifically based choices, the patient takes a greater interest in her own health. E. In pharmacy practice.
  • the patient's unique identifier can be recorded in a central registry maintained by the drug manufacturer or distributor. Pharmacists are required to consult this registry prior to dispensing the drug by prescription to avoid patients, by error or commission, receiving more than the dose or dosing confirmed as efficacious and safe in the CT.
  • the individual regression lines, individual mean score, or other individual statistics are used to calculate mean regression lines or mean statistics, or other statistical summaries for data over time, for the drug treated and placebo treated groups, or among different treatments. These are shown as lines O m -T and O m -P in Figure 1. (All similar references are to Figure 1 unless stated otherwise).
  • the points T and P are shown as an example at 1 year but can be of different time duration according to the design of the CT.
  • the lines O m -T and O m -P are then projected to T' and P', or trends, means, or other summary statistics are projected taking into account the time course of individual patients, and the CIs under each of the conditions in the research are calculated and plotted.
  • the clinical significance criteria will express the clinical aims for treatment acceptable to those familiar with the art.
  • the clinical criteria can be applied to distinguish responders and non-responders in the trial.
  • a sample of AD patients are randomly assigned blindly in a CT to receive an acetylcholinesterase inhibitor ("AchEI") or placebo.
  • the patient groups are assessed on the Alzheimer Disease Assessment Scale-Cognitive Sub-scale (AD AS-C) (Rosen et al., 1984), MMSE, and other behavioral outcome measures on three occasions, then begun on drug or placebo.
  • Patients are treated for one year and assessed at three weekly intervals at 1, 3, 6, 9 and 12 months. For each outcome measure the assessments at three weekly intervals are plotted individually for each patient and a regression slope for the pre-treatment, 1,3,6,9, and 12 month three weekly averages, is calculated. The repeated assessments are used to calculate 95% confidence intervals.
  • the regression slopes for the drug treated and placebo treated subjects are averaged separately to develop mean regression slopes for the two treatment groups.
  • the confidence intervals are applied around these mean regression equations.
  • Example 2 An analysis of a sample from an actual study of AD patient treatment is given below in order to provide a more complete illustration. In analysis of follow-up at one year of the treated group from a CT, although patient responses are less different from placebo than at the six-month end of the original research, they remain statistically significantly different from the placebo group courses projected from the original research. This one-year data set can be used to assign probabilities for patient outcomes in clinical patient care.
  • N-of-1 trials suffer from requiring a number of sequences of placebo and drug and from low power in a statistical analysis.
  • the method of the invention overcomes these difficulties by allowing sometimes only one blind, randomly assigned, placebo comparison to drug to evidence efficacy or the lack, or safety or the lack, because of the power added by Generalizability theory to within subject comparisons. Criteria of success and failure can be whether the subject's clinical course remains within or falls outside the confidence intervals from the original research model; or remaining within or falling outside the predictions from Generalizability theory from the course of the patient to date.
  • n-of-1 trials become more practical since they can be of shorter duration and increased power by incorporation within the model developed in a CT using the method of invention.
  • Example 3 In another example, a favorable profile of blood glucose induced by a drug may prove to have different long-term outcomes predicted for a patient who diets, exercises and loses weight while the same initial profile of response will deteriorate and have an increased risk of secondary consequences of diabetes mellitus in a patient who does not observe dietary restrictions, exercise, and lose weight. Or, in two patients who differ only in not losing weight even though they diet and exercise, the same degree of initial research control of blood glucose may have different long-term consequences in folio wup because initially one patient was 5% below optimal body weight and the other patient was 40% above optimal body weight.
  • Example 4 Example 4:
  • This model is applied in patient care using the same methods of assessment and statistical summary of individual patient experience used in the CT.
  • the physician using a statistical model displayed in graphical form, such as in Figure 1, or a statistical model or an arithmetic or mathematical model used in the CT(s), decides on continued treatment or discontinuation of treatment for individual patients based on a reliable plot or expression of a patient change score (perpendicular axis), time course, or other assessment, taking into account the time of acquisition (horizontal axis).
  • the physician to assure reliability may use a sequential plot or statistical summary, such as the regression slope, mean, or other scientifically, medically and statistically sound comparisons of the individual patient to the CT model.
  • the physician may predict outcomes using the probability of outcomes in the CT for patients with the same score as the immediate patient in clinical care, or trend of scores over the course of treatment, or for the group of patients within the CI of the score or trend or for all patients in the same category (in our example responder, indeterminate +, or for the mean of subjects in the research that fall within a CI generated from the treated patient's course, and so forth).
  • the physician categorizes patients as treatment responders or non-responders, or as in the future probable responders or non-responders, by inferentially applying the medically and scientifically sound methods of individual patient assessment tested and confirmed in the CT.
  • the treatment is individualized to each patient appropriate to the level of reliable and valid assessment for that patient at specific times after initiating treatment.
  • Example 5 In one example of an application of the research model generated by the methods of this invention, we assume that, taking guidance from the method of the invention, regulatory authorities approve a drug for prescription with the indication that it is to be prescribed selectively to patients who benefit.
  • the managing physician uses one or more of the research tested means of assessment to ascertain patient response and selectively use the drug or device in responders.
  • the practicing physician can use repeated single or averaged assessments to determine the patient's place in the data set generated by the research model. Based on patient A maintaining performance greater than the mean of the treated group, the physician continues treatment since the indication is that the patient resembles the group of patients who were 'responders' in the research. Another patient B who declines more than the average of the placebo group most likely is not benefiting and is discontinued as a treatment failure. For patients C, D, and so forth, with outcomes between these extremes, the physician continues or changes or discontinues treatment according to the probability in the odds ratio between the patient resembling the treated or placebo patients in the research.
  • Example 6 An important example of the application of the model developed by the method of the invention occurs when the period of clinical treatment goes beyond the period of the original double-blind CT.
  • a patient may show for 18 months a response greater than the average of the drug treated research group. At this point the patient may begin to decline. The decline may be less than, parallel to, or greater than, the mean regression equation of the placebo group in the research. The patient may still generate an odds ratio greater than 1 in the original model because of the 18 month response.
  • the physician can apply the original model projected beyond the duration of the original study to generate probabilities for the patient, can move the origin of the original model in time to the present and apply the model to the current data, and can carry out an n-of-1 trial.
  • the original model may identify the patient as currently a responder, the model with origin moved into the present may identify the current trend as probably that of a non-responder.
  • the physician hypothesizes the patient is no longer responding and increases the drug dose without effect.
  • the physician then carries out an n-of-1 trial and determines that the patient response does not differ on or off drug.
  • the physician can rationally discontinue this drug therapy or seek changes in the patient that alter the response. Accordingly, the method of invention provides improved scientific and statistical grounds for monitoring the long-term management of patients in treatment.
  • Example 7 Example 7:
  • the researchers investigating a new potential therapeutic, conduct CT(s) in which the outcome measures are used with each subject on sufficient occasions to develop statistically and clinically satisfactory CIs for the measures used in individual patients.
  • the researchers apply the methods described herein. They use the method of calculating confidence intervals (CI) for the methods of assessment both prior to and after the treatments to determine whether there are interactions between the outcome errors and treatments.
  • Drawing on standard means of assessing the outcome of treatment for the condition addressed in the patients, the investigators carry out, blind to the drug-placebo status of the research subjects, weekly assessments of the patients on three consecutive weeks, prior to randomization to drug or placebo and then at two monthly intervals over the course of the study.
  • Assessments could be blood pressures, blood chemicals, imaging, questionnaire ratings, and so forth to include potentially all outcome measures in modern medicine.
  • the model can express secular or progressive changes characteristic of the disease course. For example, the model shows a mean decline in the outcome measure of 4 per year for the placebo group and 0 per year for the drug treated group.
  • Example 8 The method of the invention can be illustrated by re-analysis ofa sample of patients from the studies of Becker et al, 1996 and 1998, which are hereby incorporated by reference as part of the present disclosure. The original studies were analyzed using current CT methods and led to the conclusion that the results could not be selectively applied to the majority of individual patients. (Becker and Markwell, 2000). The re-analysis using the methods of invention illustrates how this method develops a model that can be applied to individual patients in medical care.
  • Patient 4 declined steadily over 3 years with an Odds Ratio that favored a response that matched the placebo group. Over the 6 months prior to three years the patient declined by 1 point, during a blind placebo treatment for 6 months at three years (comparable to an n-of-1 trial) the patient declined by 1 point and in the subsequent 6 months on drug the patient declined by 1.6 points.
  • the model of the invention predicted this patient to be a nonresponder; an n-of-1 trial confirms the patient as a nonresponder because the drug-placebo difference in the n-of-1 trial does not match the trial model nor does it reach statistical probability in a test of means or slopes.
  • Patient 5 declined steadily, but over 3 years the patient's response favored the patient being a drug responder.
  • the patient showed a one point decline during two drug treatment periods and a 1.6 point decline during the placebo treatment period. These differences are not statistically different and in the model favor no evidence of a drug effect. Both patients 4 and 5 can be discontinued and another treatment considered.
  • Patient 15 declined at an average of 5 points per year for 3 years strongly suggesting patient 15 was a treatment failure.
  • patient 15 declined by 1.6 points in each of the two drug treated six month periods but by 3.5 points in the six month placebo period. Fitted to the model this does not confirm the initial interpretation that patient 15 is a treatment nonresponder and the 3.8 point projected per year difference in slopes indicates to the clinician that the drug has an effect that is benefiting the patient.
  • n-of-1 trials illustrate how this methodology can be used to obtain double-blind longitudinal data to expand the research data base of the model and thus supplement the original drug efficacy evidence. It is probable that patient 15 would have been discontinued as a treatment failure if a clinician had only the data of the original research analysis (Becker et al., 1996, 1998) and that patients 4 and 5 may have remained on treatment — treatment that did not benefit them and an unnecessary medical care expenditure. If additional n-of-1 trials are conducted on the patients at 2 and 3 years treatment, a statistically significant altered model for 2 and 3 years might emerge or loss of efficacy might be confirmed.
  • the method of invention can be employed in reinterpretation of currently analyzed trials as hereinafter described.
  • a physician managing an Alzheimer's disease patient finds no change in Mini-Mental State Examination scores justification for switching drugs since the advertising for the product — based on current methods of CTs and their analysis — specifies a "4-point improvement" over placebo treated patients. If the physician has analysis of the invention available, he would know that this patient's six-month score predicts with a high probability one of the most successful available longer term treatment outcomes and that he could confirm this prediction using the model generated by the method of the invention to interpret an n-of-1 trial.
  • a physician treating a depressed patient finds the patient not "fully" recovered after one month.
  • the physician knows that customary practice and research evidence require at least 6 to 12 weeks of treatment to minimize the chances for relapse in this first depression for this patient.
  • the physician agrees to try a new drug. If the physician had available the individual clinical courses of patients treated in the randomized clinical trials as would be developed by the method of the invention, the physician would realize that the patient's progress predicts with high probability full and lasting recovery after three months of drug treatment.
  • Example 11 In CTs, the method of the invention for a newly approved disease-modifying antirheumatic drug provides a range of patient courses and for each course the probability of ultimate improvement of rheumatoid arthritis, given the current dose and duration of treatment at that dose.
  • the model also provides the probability of maintaining improvement at different levels of dosage reduction once maximum benefit has been reached.
  • an electronic medical record system routinely queries a patient and enters these assessments with the laboratory studies and clinical findings to monitor the current treatment in terms of whether it offers the patient the highest probability of optimal outcome long-term.
  • the physician's assessments abbreviated by the demands of a busy practice, are supplemented by the patient's self reports and the automatic analysis using the model developed by the method of the invention.
  • Example 12 Example 12:
  • An anxious or personally concerned patient who wishes to participate actively in her own health care explores the model of the invention derived from modified, randomized, controlled trials and traditional clinical trials relevant to her condition using Internet access to MedlineTM and Medline plusTM.
  • the better informed patient can select among treatments that seem most soundly justified to her and more easily engage in final decision making with the physician.
  • the patient already in treatment can compare her progress with the research results in other trials.
  • the patient better understands both her progress as a predictor of ultimate outcome using the method of the invention randomized controlled trials for her freatment and the place of her treatment among the options available for a person with her condition.
  • Example 13 Medical care is opened to the patient participating in the applications of scientific evidence in her care; the patient is more fully informed; and the physician deals with a better educated patient without the burden of summarizing the relevant literature for the patient. Less mystified, more centrally involved, better able to reach sound preliminary scientifically based choices, the patient takes a greater interest in her own health.
  • Example 13 A new treatment shows equal efficacy to an earlier more expensive treatment for a medical condition. A small margin of additional mean benefit for the old treatment is disregarded by funders of medical care because of the high costs of the old treatment and the vague benefits.
  • the method of the invention applied to a clinical research study of the old treatment identifies significant additional efficacy for about 25% of patients and shows that a brief trial to identify responders from non-responders adds only about 20% to the cost of treatment of each benefited patient.
  • approve the old treatment used in conjunction in accordance with the invention In view of the clinical significance of the benefits, and the ability to control the costs of each successfully treated patient, insurers, pharmacy committees, and other groups that control drug use, approve the old treatment used in conjunction in accordance with the invention.
  • An inexpensive medication effective in some patients with a given medical condition competes with an expensive medication more generally effective and free of adverse events.
  • An organization responsible for funding medical care wishes to improve the overall quality of the care and to avoid unnecessary expense.
  • the organization agrees with the pharmaceutical manufacturer of the more expensive product that if they will develop a method of invention model for the effective, safe, and economical, use of the inexpensive and patented medications, the organization will approve both for use and reimbursement.
  • the manufacturer demonstrates how specific indicators of outcome can be followed in individual patients to identify, early in treatment, those who will reach maximum benefit on the inexpensive medication and those who will require the more expensive medication.
  • This model becomes the standard controlling use of these medications in the medical care provided by, or reimbursed by, the funding organization.
  • the scientifically highest quality medical care is provided to patients at the lowest possible cost for such quality care.
  • Interfacing the electronic medical record with an electronic record of randomized controlled trials in accordance with the invention allows treatment decisions to take into account the specific probabilities for patient outcomes from different treatments and to monitor the progress of each patient in relation to the scientific evidence of individual patient courses and outcomes evidenced in the randomized controlled research trials of the invention. Additional data about other patient outcomes can also be made available to inform individual patient decision making and to monitor clinical practice experience in terms of research trial experience.
  • the method of the invention integrates the aims of evidence-based medicine and electronic medical records to capitalize on these advantages by providing patient care that is scientifically and individually integrated.
  • Example 16 Using the method of the invention, individual patient response data can become available in pharmacies to inform or control drug dispensing by prescription.
  • Dr. A instructs her patient Mr. B to monitor his blood glucose and blood pressure regularly as part of the management of Mr. B's Diabetes Mellitus Type II and Essential
  • Dr. A recommends to Mr. B dietary restrictions, an exercise program, goals for weight loss, and prescribes an oral hypoglycemic medication and an antihypertensive medication.
  • Mr. B uses monitors for blood glucose and blood pressure designed for the home. These monitors can be connected by phone to an Internet site.
  • Dr. A maintains an electronic medical record for each patient. The Internet site integrates the reports of Mr. B's self monitoring into the medical record and analyses the findings in relation to Mr. B's clinical course and in relation to comparable patients in the randomized controlled trials that determined the safety and efficacy of the medications.
  • Mr. B After six-weeks treatment for his hypertension at an office visit Mr. B points out that his neighbor "got back to normal blood pressure already and I'm not there even though we started together.” Dr. A sees the progress but wonders if something more should be done for Mr. B. She considers changing his medication. Before doing so she compares his course to the course of research patients. The comparison indicates that he has an 80% — 4 to 1 odds — that he will be at a blood pressure of 140/85 within 3 months and improve further for an additional 3 months. Since he has not demonsfrated interfering adverse effects from his current medication, she shares the information with him and they decide to remain on the current medication.
  • Mr. B forwards a high blood glucose reading.
  • the Internet site asks if he has strayed from his diet or skipped his exercise that day. Mr. B reviews his last meal and notes that he conveniently overlooked the glycemic index of a treat. He is reminded immediately of the cause of his difficulty and becomes more vigilant in his self care.
  • a drug company uses the method of this invention to record the daily blood glucose profiles of each research patient.
  • the research provides both individual profiles of response and the incremental accrual of, and total daily, excess glucose exposure over time within those profiles.
  • the research goes on to key these exposures to surrogate markers of complications by long-term follow-up of research patients and from other research sources.
  • the data from a monitor worn by Mr. B is entered into his electronic medical record over the Internet and interpreted with the method of the invention. Dr. A then can evaluate Mr. B against this data base and achieve closer control of blood glucose with the new medication.
  • Patient A at 3 months has a single MMSE of 25 compared to a single pre-treatment MMSE of 21. This is 1/4 point above the upper limit of the single assessment CI around the placebo mean regression line at 3 months. A is a responder and treatment is continued.
  • Patient B at 3 months has an average score of 15 on the MMSE (scores on weeks 10, 11, 12 are 15, 13, 17) compared to an average immediately before starting the medication of 18 (three consecutive scores of 20, 19, 15). This score change falls below the lower 95% CI for mean scores of the placebo group characterizing the patient as a probable treatment failure.
  • the physician decides to follow the patient for another month, finds the patient continues on the same rate of decline with a mean score of 14. The physician blindly discontinues treatment for a month by arranging for the pharmacist to provide a placebo. The patient remains at 14 for this month. They accept the patient as a treatment failure. The physician turns to another treatment.
  • Patient C has already had two years of freatment with another drug for AD but has declined from 26 on the MMSE to 19.
  • the patient has another form of treatment with a decline to 16 in 6 months. This too is regarded as a failure and the model from the method of the invention is used to determine whether this patient can benefit from freatment.
  • the patient at 12 months has a single MMSE of 12 compared to a single pre-treatment MMSE of 16. This is 4 points decline in a year, the expected placebo decline in the CT model, a rate of decline that projects that, if sustained, the patient will have a higher probability of being a treatment failure than a treatment success.
  • the physician arranges with the pharmacist to dispense, physician and patient blind to the condition, drug or placebo to the patient over the next year alternating the condition randomly every 3 months.
  • the physician selects this course because in the research model developed by the method of the invention (see Figure 1) even some patients that were apparent failures were benefiting from drug.
  • the physician blindly assesses the patient every three months and then plots the course using the model. At the end of the two years the patient has an MMSE score of 10.
  • the physician has predicted the patient will be a clear treatment failure from the 4 point initial decline at 1 year; in spite of 6 months on placebo the two year assessment does not confirm that prediction.
  • the patient declines 0 and 1 points, and in two three month placebo periods, the patient declines 2 and 3 points.
  • the data fitted to the model do not support his prediction that drug treatment will be ineffective.
  • the patient is continued on medication with the prediction of no more than 2 points per year decline because this is the confidence interval from the patient's course fitted to a 1 point per year projected decline from the n-of-1 trial. If the decline does not exceed a rate of 2 points per year, the physician receives support from the model that the patient receives some benefit from the drug.
  • Patient D has been treated using the model from the illustrated CT(s) for 2 years.
  • she scored 25.
  • she scored 26 as a mean of three ratings.
  • she scored 21 as a mean of three ratings.
  • Her physician worries that the rate of decline between year 1 and 2 reflects a loss of drug effect.
  • the patient was a responder at year 1, but is now in the indeterminate + group.
  • the physician follows the patient with mean ratings every 3 months for the next year.
  • the patient has regression lines fitted to the data by a computer program available to the physician in a hand-held or desk-top computer. Using all assessments, the equation shows at 3 years an MMSE score change of -4 placing the patient strongly in the responder group in the model.
  • the equation shows a MMSE 3 year score of -7 which is -1 CI below the mean treated group model projection from the CT, but +2 CIs above the projected placebo decline. This reassures the physician that benefit is probably ongoing. If this second regression equation had shown over time the difference in the patient score from the projected mean placebo regression projection progressively growing smaller, the physician would be supported by the model to change the patient's status from responder (at 1 year) to probable non-responder with continued treatment. This would justify the physician reevaluating the patient's current treatment: using an n-of-1 trial; changing treatment; and so forth.
  • Patient E has an initial single assessment of 18, at three months 17, at 6 months 15, at 9 months 14.
  • the patient shows a trend that will clearly indicate probable treatment failure during the 2 nd year if the trend is maintained. Since the patient will be severely cognitively impaired if the trend continues, the physician considers the patient a failure on this treatment and turns to other treatments that have shown promise in AD.

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Abstract

L'invention concerne un système et un procédé destinés à des chercheurs médicaux effectuant des recherches au niveau d'une procédure ou d'une intervention médicamenteuse, ou de l'efficacité, la sécurité, l'aspect économique ou l'utilisation d'un dispositif, aux fins de développement et de test d'un modèle de décision déterminant de manière individuelle pour chaque patient l'efficacité, la sécurité, les avantages économiques et l'utilisation probables de médicaments ou de dispositifs médicaux. Le modèle met en oeuvre des études permettant de déterminer la fiabilité des mesures, du critère de signification clinique, du critère de signification statistique, des études de la validité interne d'évaluations de patient placé aussi bien dans des conditions régulées de placebo en double aveugle que dans des conditions régulées de non placebo non en double aveugle. L'invention concerne également des procédés permettant de confirmer les prévisions du modèle d'essai clinique et des études de prévisions à long terme de statut salutaire, à partir de mesures de résultat, ainsi que d'essais cliniques ou d'autres conceptions de recherche médicale permettant d'identifier la réponse de chaque individu au traitement. Le modèle de décision permet d'améliorer la mise en oeuvre de normes scientifiques et médicales de soins médicaux de patients dans un cabinet médical et peut être appliqué dans des soins médicaux, l'élaboration et la régulation de médicament, le financement de soins médicaux, des dossiers médicaux électroniques et dans une officine pharmaceutique.
PCT/US2001/049457 2000-12-26 2001-10-26 Systeme et procede d'elaboration de medicaments destines a une utilisation selective de medicaments chez des individus, patients repondant au traitement et applications du procede dans des soins medicaux Ceased WO2002051354A2 (fr)

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US8489336B2 (en) 2002-09-16 2013-07-16 Optimata Ltd. Techniques for purposing a new compound and for re-purposing a drug
WO2004049217A1 (fr) * 2002-11-27 2004-06-10 George Medica Pty Ltd. Systeme de realisation de tests cliniques
WO2006050980A3 (fr) * 2004-11-15 2006-08-31 Novo Nordisk As Procede et appareil permettant de surveiller des effets a long et court termes d'un traitement
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US12396667B2 (en) 2014-06-13 2025-08-26 Vccb Holdings, Inc. Alarm fatigue management systems and methods
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US10762171B2 (en) 2014-08-28 2020-09-01 Nanthealth, Inc. Patient sensor data exchange systems and methods
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US11915198B2 (en) 2014-08-28 2024-02-27 Nanthealth, Inc. Patient sensor data exchange systems and methods
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CN112639992A (zh) * 2018-08-03 2021-04-09 卡米洛英国竞标有限公司 用于确定要制造的药品的设备、方法和计算机可读介质
CN116580797A (zh) * 2023-05-15 2023-08-11 北京利久医药科技有限公司 一种临床试验数据的快速比对方法
CN116580797B (zh) * 2023-05-15 2023-10-31 北京利久医药科技有限公司 一种临床试验数据的快速比对方法

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